The new era of supply chain management is characterised by key change drivers, e.g. Industry 4.0, and post-COVID-19 VUCA (volatility, uncertainty, complexity and ambiguity) business environment, in addition to the rising requirements for sustainability, responsiveness and customer centrism. An important and topical question in this context is what supply chain managerial competence logistics managers need to possess in order to enhance their individual performance in the new era. This question is addressed in this paper, which also explores the nexus of supply chain managerial competence expectation and possession upon which human resource development strategies are proposed accordingly.
The survey research design is adopted to empirically examine logistics managers’ supply chain managerial competence in the new era, and the forward-backward translation process was strictly followed. Data were collected through a survey conducted with owners or managers of Vietnamese firms whose business is in the logistics and related business areas, and 269 valid responses were used for analysis.
Results indicated that the proposed profile of four groups (foundation, core, specialist and technology-IT) and 38 competencies are valid and important to the individual performance of logistics managers in the context of Vietnam, which supports the tenet that logistics managers in the new era need to have a well-rounded profile of competencies, including those derived from contemporary change drivers. It was also found that the foundation competency group is perceived as more important than others, which is context specific given the current logistics development in Vietnam. Besides, it was also revealed that respondents in this research currently possess those competencies at a level which is lower than their perceived importance. An Importance-Possession (IPM) Matrix of Competency Development was mapped accordingly.
The generalisation of this study would require further empirical examination from similar studies in other contexts, i.e. in other manufacturing and service sectors as well as in other developing and developed countries where logistics development is at different stages.
This research provides insights into the current competency profile of logistics managers in Vietnam, which can assist senior management with human resources development in their firms. Specifically, it is essential that Vietnamese logistics firms focus on providing education and training opportunities, both internally and externally, to enhance the level of possession of all competencies whose gaps between perceived importance and possession are the largest across the groups, especially those in the Maintaining Sustainably and Growing quadrants of the IPM.
Firstly, this research introduces an improvised framework of logistics managers’ supply chain managerial competence adopting the contingency approach, contributing to expanding the body of knowledge on how the competency profile of logistics managers should be developed. Secondly, the IPM matrix of competencies introduced in this research can be used as both the conceptual and managerial tool to classify and prioritise competencies for various purposes, e.g. education, training and policy implementation based on the nexus of supply chain competence expectation and possession.
1. Introduction
It has long been acknowledged that logistics and supply chain management is essential in the national economy of all countries, regardless of their economic structure, given the time and place utilities that they create. In a national logistics system, key elements include infrastructure, institutional framework, shippers/consignees and service providers (Banomyong et al., 2015). Placing in the centre of this system is logistics professionals whose competence has a direct effect on those key elements of the system, their interactions, and the efficiency and effectiveness of the system as a whole. Therefore, developing the competency profile and equipping logistics professionals with those competencies are key in the education and training agenda of both micro (i.e. firm) and macro (i.e. country) levels.
In the logistics and supply chain management discipline, research on logistics competence has a long history and is still evolving. Since the 1990s, notable studies such as La Londe (1990), Williams and Currey (1990) and Murphy and Poist (1991a) have already highlighted that logistics managers require a range of skills to be effective. Scholars have continued their research in this knowledge domain until today, in the age where many new technologies and tools become available, and thus supply chain talents, experts and graduates are highly sought after (Merkert and Hoberg, 2023). In this respect, it is argued that while technologies are accessible to firms, competencies need to be developed in not only those firms but also their supply chains for these technologies to be fully exploited (Gammelgaard, 2023).
Meanwhile, some recent studies have also implied that logistics professionals would need to constantly update their competence profile in responding to global and industry challenges and opportunities, and this applies in various sectors such as maritime logistics (Hussein and Song, 2023), aviation logistics (Merkert, 2023) and warehousing (de Koster, 2023). This also applies to some topical developments such as the low-carbon economy (McKinnon, 2023) or supply chain resilience (Kiers et al., 2022). What can be derived from these recent studies is that there is still a need for a comprehensive and well-rounded, and not on a piecemeal basis, supply chain managerial competence framework which is universally applicable to logistics and supply chain professionals in different sub-sectors of the industry, and encompasses change drivers of the contemporary business environment. Such a framework corresponds well to the approach to examining key competencies of logistics and supply chain management professionals from the lifelong learning perspective (Kotzab et al., 2018) and, once validated, would facilitate not only the development of relevant training and education programs but also the analysis for improvement within and between organisations and sub-sectors of the industry. Besides, such a framework can also be used as the foundation for further exploration of strategic HRM policies once the potential gaps between the possession and importance levels of competency in this framework are identified.
Logistics and supply chain management has undergone tremendous changes in the last decades corresponding to the turbulent, competitive and evolving market environments. In recent years, the application of various Industry 4.0 technologies in multiple economic sectors, as well as the resulting changes as a result of the recent COVID-19 pandemic such as intensified e-commerce and increasingly focused supply chain resilience have added complexity to the management of logistics and supply chain operations. As a consequence, a pertinent question is what supply chain managerial competence logistics managers need to possess in order to enhance their individual performance in the new era, with change drivers, e.g. Industry 4.0 and post-COVID-19 pandemic creating volatility, uncertainty, complexity and ambiguity (VUCA) business environment.
This paper aims to address the aforesaid question in the context of Vietnam and also explores the nexus between the perceived importance and current possession level of these competencies by Vietnamese logistics managers, upon which human resource development strategies can be proposed accordingly. While the importance of logistics has been growing in Vietnam, and although the country’s LPI (Logistics Performance Index) ranking has improved in recent years, it is not stable and slipped in 2023. As logistics competence, in which competencies of logistics managers are a key contributing factor, is an essential component of the index, the investigation of this issue in the context of Vietnam will contribute some insights both in terms of knowledge building and management practice. The remainder of the paper is structured as follows. First, a literature review and conceptual framework development is presented adopting the contingency approach. This is followed by a brief review of logistics development in Vietnam. Details of research methodology are presented next, followed by analysis of data and findings which are then discussed in the next section. Finally, the paper concludes with a summary of findings, and academic and managerial implications.
2. Literature review and conceptual framework development
2.1 Competence of logistics managers
The term “competence”, first appeared in White (1959) as a concept for performance motivation, and is often examined as a multifaceted construct, denoting it as skill, knowledge, ability, behaviour and personality trait.
Today, the concept “competence/competency” has been used widely in many research contexts and business sectors, i.e. education (e.g. Gey et al., 2023, Vitello et al., 2021), accounting (e.g. Schöning and Mendel, 2023, Parson et al., 2020), information technology (e.g. Rodríguez-Abitia et al., 2022, Assyne et al., 2022), project management (e.g. Rosamilha et al., 2023, Alvarenga et al., 2019, Tabassi et al., 2016), production technology (e.g. Kannan and Garad, 2021, Siegert et al., 2020) and hospitality (e.g. Marneros et al., 2020, Suhairom et al., 2019, Shum et al., 2018). In the domain of logistics and supply chain management, there have been several studies on the competency profile of logistics professionals at various levels, in which a recent study by Mageto and Luke (2020) provides a systematic summary.
Research on the competency profile of logistics managers was perhaps first marked by the well-known Business, Logistics and Management (BLM) framework originally developed by Poist in 1984 (Biljana et al., 2017). Following this, Murphy and Poist (1991a) presented all skill requirements for logistics professionals under three main categories, namely, business, logistics and management skills. The first version of the BLM framework considered a total of 83 competencies. Further development of this framework and its application were also carried out in their subsequent studies (e.g. Murphy and Poist, 1991b, 1993, 1998, 2006, 2007). Other researchers such as Lin and Chang (2018), Mangan et al. (2001), Razzaque and Sirat (2001), Thai et al. (2011), Thai (2012), Thai et al. (2012) also used and modified the BLM framework in their research in the contexts of Taiwan, Ireland, some Asian countries, Australia and Singapore to discuss the required competencies for managers in the field of logistics and SCM. Researchers also modified and contextualised the BLM framework to suit specialised disciplines such as container shipping (Thai and Yeo, 2015) and port (Thai et al., 2016), in which competencies in each of the BLM groups are classified into those of generic and maritime or port-specific nature. Researchers also modified and expanded the BLM framework in specialised areas, for instance, in the 3PL business in Indonesia in which a framework that consists of management, logistics, business and information and communication technology competency categories was examined (Sangka et al., 2019).
Meanwhile, researchers also advocated other groupings of competencies required for logistics and supply chain managers and professionals, apart from the BLM framework. In this respect, Gammelgaard and Larson (2001) identified 45 supply chain management competencies that are required for logistics managers and grouped them into interpersonal/managerial basic skills, quantitative/technological skills and SCM core skills. Giunipero and Pearcy (2000) described seven key skill sets for supply managers and emphasised the most important skills for them. In further work, Giunipero and other researchers continued examining specific skill areas for supply managers (Giunipero et al., 2005, Giunipero et al., 2006). Myers et al. (2004) considered skill requirements for logistics managers categorised into the following groups: social, decision-making, problem-solving and time management skills. Mangan and Christopher (2005) also presented two key knowledge areas (general and logistics/SCM specific) and key competencies/skills required by logistics and supply chain managers. Richey et al. (2010) and Van Hoek et al. (2002) focused on soft aspects only, such as emotional and social skills. Shou and Wang (2015) covered a wide range of competencies using the categories of generic skills, functional skills, SCM qualifications and leadership, SCM expertise, and industry-specific and senior management skills. Meanwhile, using the shadowing and practice theory, Derwik et al. (2016) concluded that logistics and supply chain managers use business managerial, generic and behavioural competencies in practice rather than supply chain management expertise. By employing the adaptive choice-based conjoint (ACBC) experiment, Flöthmann et al. (2018a, b) stated that SCM knowledge and analytical and problem-solving abilities were the most important competencies and were considered more important than general management skills. Recently, a study of Wagner et al. (2020) categorised skill and knowledge requirements of entry-level logistics and supply chain management professionals into generic, functional, and analytical, environmental and security skills, and also revealed that there are major gaps between graduates in Spain and Ireland where there are different industrial and managerial contexts.
There have been efforts to summarise and synthesise logistics and supply chain management (L&SCM) competencies in the literature in a systematic and structured manner. Notably, by reviewing 98 publications, Derwik and Hellström (2017) derived a framework of functional, relational, managerial and behavioural competency groups spanning across individual, intra-organisational and inter-organisational levels. While acknowledging this framework, Campos et al. (2019) however also reviewed 25 publications on the theme to propose 24 general and specific competencies, and examined the level of importance and use of those competencies by managers from 34 companies in the mid-sized supermarket sector in the metropolitan region of Natal, Brazil. An interesting finding from this research is that the level of use was below the level of importance for all competencies, and respondents also rated general competencies more important than specific competencies. This contradicts Flöthmann et al. (2018a, b) but aligns with several earlier studies, such as Derwik et al. (2016). Meanwhile, Gámez-Pérez et al. (2020) proposed an international university–industry collaboration model to develop supply chain management competences and identified four key supply chain competence groups mainly validated and categorised in some earlier studies, such as Derwik and Hellström (2017).
Professional associations in the industry also participate in the quest to identify necessary competencies for logistics and supply chain professionals and develop them into industry occupational standards. In this connection, the American Production and Inventory Control Society (APICS, now the Association for Supply Chain Management, ASCM) developed five competence models for professionals in the field of operations management, specifically for supply chain managers, materials managers, buyer-planners, distribution and logistics managers, and master scheduling managers (APICS (The Association for Operations Management), 2014). On another note, it is acknowledged that, by focusing on what managers do rather than what management is, one can ask what competencies are necessary for logistics managers (Derwik et al., 2016). According to Luthans et al. (1988), successful and effective managers spend far less time on traditional management activities, such as planning, decision making and controlling, in comparison with the average manager. Instead, effective managers spend more time on networking, routine communications and human resource management. Mintzberg (2009) acknowledged this multifaceted role and presented personal, interpersonal, informational and actionable competencies as appropriate attributes for a manager.
Although managerial competence has been studied extensively in the extant literature (Manxhari et al., 2017, Chong, 2008, 2013), it can be seen that the topic in the context of L&SCM is still evolving with different models and approaches of competencies required for logistics and supply chain managers in various contexts. This is rather interesting, noting research evidence which shows that L&SCM competence has a substantial effect on business performance and financial competitiveness (Flöthmann et al., 2018a, b, Ellinger et al., 2011, Aquino and Draper, 2008, Bowersox et al., 2000), and executive engagement plays an important role in enhancing firm’s competitive advantage through supply chain competencies and capabilities (Birou and Van Hoek, 2022). Therefore, further research is required to map out the competency profile of logistics and supply chain managers given the contingent change drivers in the new era.
2.2 The change drivers of logistics and supply chain managers’ competence
The requisite L&SC manager competencies have changed in recent decades owing to profound business transformations in the field, for example, the globalisation of supply chains, continued outsourcing, and the widespread adoption of lean practices or technological development (Christopher, 2012). The introduction of Industrial Revolution 4.0 (Industry 4.0) has brought about a widespread application of various technologies which, in turn, impose implications on technology-related competencies to L&SC managers. Meanwhile, the negative impacts of the COVID-19 pandemic on various business sectors, including the logistics industry, also require the upgrade and/or acquisition of new competencies to adapt and cope with the changes and challenges in the VUCA business environment. Hence, this section discusses the change drivers and implications on the competency profile of L&SC managers.
Due to the significant impacts of Industry 4.0 on the whole supply chain, logistics would be the most appropriate application area for Industry 4.0 as it is directly related to the success of the new industrial revolution. In particular, the fourth revolution relies much on the use of digital product models such as smart products, 3D printers and autonomous vehicles to meet the customer requirements of smart factories, which involve logistics (Douaioui et al., 2018). Due to the technological development in Industry 4.0, many firms have been implementing the so-called “Smart logistics or Logistics 4.0”, which evolved around 2011 with the aim of meeting changing customer requirements and providing sustainable logistics solutions (Winkelhaus and Grosse, 2020). It is undeniable that Logistics 4.0 capability requires the development of dynamic capabilities such as technological capabilities and environmental capabilities to enable digital technologies and execute plans (Winkelhaus and Grosse, 2020, Gammelgaard, 2019). This new paradigm is the result of the increased use of the Internet that enables the communication between machines and humans in real-time and the use of what is known as advanced digitalisation (Barreto et al., 2017a, b, p. 1248). It is evidenced in many studies that the adoption of information and communication technology (ICT) has become inevitable in the supply chain, especially in logistics and production operations, to decentralise decision making, avoid inaccuracies and facilitate faster processes (Barreto et al., 2017a, b). Notably, the evolution of logistics must involve the integration of the internet of Things (IoT), Internet of Services (IoS) and smart factory (Douaioui et al., 2018) in specific logistics systems, i.e. resource planning, warehouse management systems, transportation management systems, intelligent transport systems and information security (Barreto et al., 2017a, b). Besides, artificial intelligence (AI) applications have been used widely in logistics and supply chain management and helped improve decision making and facilitate the automation of workflows (Boute and Udenio, 2023). Those require logistics managers to update new skills, knowledge, traits and competencies for successful managerial performance such as computational and analytical skills (Barreto et al., 2017a, b, p. 1249), or even just specialised in analysing computer outputs (Boute and Udenio, 2023). The increasing necessity of computational and analytical skills, as well as technological systems integration, will change the common profiles of the logistics managers in the industry (Saidi et al., 2020, p. 279, Barreto et al., 2017a, b, p. 1249). IT (or sometimes ICT) competencies are the skills and abilities needed to work with information technology systems. Other needed competencies would be the understanding and use of logistics software, multitasking ability, contingency competence and interoperability (the ability of machines, devices, sensors and people to connect and communicate with each other via the internet of Things – IoT).
Meanwhile, the COVID-19 pandemic has challenged logistics and supply chain management substantially and provided additional impetus for Industry 4.0. With the move to working from home and social distancing, technological augmentation has become increasingly valuable and managers may have “jumped” the learning curve. The question will be to what degree managers will be tempted to revert back to “old ways” or if they will find themselves building upon new capabilities and skills, accelerating the transformation (van Hoek et al., 2020, p. 2). This requires logistics companies/managers to upgrade the change management and/or contingency skills to cope with the “sudden changes” of the business environment especially in the context of the VUCA world. In this connection, Grzybowska and Anna (2017) argued that logistics managers should possess key competencies, i.e. creativity, entrepreneurial thinking, problem-solving, conflict solving, decision-making, analytical skills, research skills and efficiency orientation. In the aftermath of the COVID-19 pandemic, the requirement for other important logistics and supply chain management competencies has also emerged in specific contexts, such as supply chain collaboration for humanitarian logistics operations (Fard and Papier, 2023), or automation, technical skills and supplier relationship management, among others, to respond to strategic changes required for enhancing supply chain resilience (Kiers et al., 2022).
Sustainability is another noteworthy change driver that has an implication on logistics and supply chain managers’ competence in the new era. In recent years, there has been a plethora of research conducted on supply chain sustainability and circular supply chain management, as reviewed in the study of Farooque et al. (2019), although the implications on logistics and supply chain managers’ competence were not identified in the list of topics for further research. However, a few researchers managed to examine these implications in specific areas, such as Schulze et al. (2019) who identified key competencies related to sustainable purchasing and supply management such as supplier relationship management and basic sustainability knowledge, or McKinnon (2023) who suggested that logistics executives need to possess expertise in the planning and implementation of sustainable logistics to prepare for the low-carbon economy. Meanwhile, Richey et al. (2022) argued that logistics and supply chain management as a business discipline depends on the development of foundational supply chain management perspectives embracing a focus on responsiveness, which is attributed by key dimensions of the discipline literature, i.e. agility, flexibility, adaptability, improvisation and resilience. To this end, this focus resonates with the whole purpose of SCM, i.e. creating customer value and the core of SCM, i.e. supply chain optimisation and inter-organisational collaboration which are still relevant today (Min et al., 2019). These change drivers, both contingent and ongoing, imply that L&SCM managers would need to be upskilled and reskilled so as to enhance supply chain performance – the core of their firms.
Overall, the aforesaid social and business, as well as technology trends, would have tremendous impacts on the future of jobs and competency requirements in all economic sectors, including logistics and supply chains. The most widely discussed implications are that some conventional jobs will disappear while new jobs are introduced, and competency profiles associated with jobs will also change accordingly. Meanwhile, the current workforce including logistics managers will also need to be re-skilled and up-skilled where appropriate to meet the job market and economic demand. Those above-mentioned skills may not be entirely new to some logistics and supply chain managers, but in the context of Industry 4.0, sustainability, resilience, responsiveness, customer centrism and the VUCA world, they should be acquired or upgraded at higher levels to meet or satisfy the actual requirements in each organisation.
2.3 Logistics managers’ supply chain competence profile in the new era: a contingency approach
The contemporary business environment has been evolving with change drivers affecting how firms’ businesses are being operated and managed. In this connection, not only the firms’ “infrastructure” i.e. facilities and equipment would need to be upgraded or with new investments, but their “superstructure” such as human resources would require their competencies to be updated or equipped with new supplements corresponding to the change drivers. It is therefore argued that the development of logistics managers’ supply chain competence will need to take a contingency approach to ensure a comprehensive and pragmatic inclusion of essential competencies required. The contingency approach to management questions the universal applicability and posits that good management will look different based on situational variables (Moniz, 2010), as there is no universal management approach in organising a firm’s resources (including profiling a manager’s competence), leading a corporation or making decisions given the constant changes. This has been formalised by various known scholars notably Morgan (1997) who argued that there is not one best way of organising, since the appropriate form depends on the kind of task or environment one is dealing with, or Fiedler’s contingency model of leadership (1993) which describes the relationship between leadership style and the favourableness of the situation, with numerous applications both in academic research and in management practice.
The contingency approach has been adopted in some studies in which competency development was involved. For instance, Müller et al. (2024) advocated a contingency perspective on four archetypical competency portfolios related to digital transformation leadership, i.e. the challenger, the bricoleur (those who support operational efficiency by using digital technologies), the organiser and the competitor, arguing that this requires different competencies depending on the transformation drivers and goals. Liu et al. (2016) also employed both contingency and configuration perspectives to conceptualise and operationalise the fit between appropriate information technology (IT) competency and supply chain integration (SCI) of a firm in inducing superior firm performance. Meanwhile, the contingency theory was also employed to derive the competence loop framework explaining how an organisation can use learning strategies to support competence exploration/exploitation (Medina and Medina, 2015). It is consistent in the literature that employing a contingency approach in underpinning competence development for the organisational workforce is an appropriate choice.
Although logistics managers’ supply chain competence has been researched for quite a while in the extant literature, it is also apparent that the topic is still evolving with various models and approaches. As evidenced in the literature, the supply chain competence of logistics managers is a multidimensional construct that consists of various aspects of the logistics managers’ knowledge, skills and abilities. In this connection, Mageto and Luke (2020) conducted a systematic literature review and identified 270 SCM competencies which were categorised using various frameworks, including business-logistics-management, T-shaped, expertise level, SCM skills and hard and soft skills. Meanwhile, professional peak bodies in the industry developed competency models for logistics and supply chain managers incorporating competencies that are structured within the foundational, profession-related and occupation-related groups (APICS (The Association for Operations Management), 2014), or foundational, core, and technical groups (Supply Chain Canada, 2020), or key knowledge areas of core generic areas and specialist key knowledge areas (The Chartered Institute of Logistics and Transport (CILT), 2017). The common observation of these frameworks is that the competencies in the profile of logistics managers should include not only those that constitute their capability reflected in the foundation (or generic), core and specialist (or technical) levels, but also those derived from the emerging economic, social and technological environments, which are constantly evolving. The latter implies that logistics managers in the new era would need to possess not only the traditional foundational business and management related, and hard-core logistics related specialist competencies, but also evolving SCM-related core competencies as well as those emerging from the contemporary economic, social and technological environments.
Employing the contingency approach, and incorporating and leveraging on the above, it is envisaged that four cornerstones of competency would constitute the supply chain managerial competence of logistics managers of the future, as depicted in Figure 1. These include foundational competencies, core competencies, specialist competencies and technology-IT competencies. The foundational competencies are sets of business and management proficiencies related to workplace and leadership, as well as academic and personal effectiveness, as the “soft competencies” that prepare the solid foundation for logistics managers to be successful in their job (Supply Chain Canada, 2020, van Hoek et al., 2020, Mageto and Luke, 2020). The core competencies, as the title dictates, include core SCM-related proficiencies that logistics managers in the new era would need to possess so as to manage their firms’ supply chains effectively. Given the current focus on business management from the supply chain perspective, these SCM core competencies, including those emerging and critical in the VUCA business environment, are essential to logistics managers (Kiers et al., 2022, Hallikas et al., 2021, Kotzab et al., 2018). Meanwhile, logistics managers’ supply chain managerial competence should also include the hard-core logistics specialist competencies upon which the effectiveness of their day-to-day operations relies (Supply Chain Canada, 2020, Mageto and Luke, 2020, Derwik et al., 2016, APICS (The Association for Operations Management), 2014, Murphy and Poist, 2007). In addition, given the widespread applications of Industry 4.0 in logistics and supply chain management nowadays, it is envisaged that technology-IT competencies should also constitute the all-rounded competency profile of the logistics managers in the new era. A logistics manager with technology-savvy capability would be indeed essential in the business environment, which is influenced by fast changing technological developments (Gaudenzi et al., 2021, Hallikas et al., 2021, Holubčík et al., 2021, Sundaram et al., 2020).
The centre of the figure shows a text box labeled “Supply Chain Managerial Competence”. Surrounding this central box are four oval-shaped boxes positioned around it. At the top left, an oval labeled “Foundational Competencies” is present. Similarly, at the top right, another oval labeled “Core Competencies” is present. On the bottom left, the oval labeled “Specialist Competencies” is present, and at the bottom right, an oval labeled “Technology - I T Competencies” is present. All these four ovals are connected by double-headed arrows, and arrows arise from each of the ovals and point toward the central box.Logistics managers’ supply chain competence framework
The centre of the figure shows a text box labeled “Supply Chain Managerial Competence”. Surrounding this central box are four oval-shaped boxes positioned around it. At the top left, an oval labeled “Foundational Competencies” is present. Similarly, at the top right, another oval labeled “Core Competencies” is present. On the bottom left, the oval labeled “Specialist Competencies” is present, and at the bottom right, an oval labeled “Technology - I T Competencies” is present. All these four ovals are connected by double-headed arrows, and arrows arise from each of the ovals and point toward the central box.Logistics managers’ supply chain competence framework
Table 1 details the list of foundational, core, specialist and technology-IT competencies, which are required to constitute the supply chain competence of logistics managers in the new era. The list consists of 38 competencies that were derived from a comprehensive and systematic process of literature reviewing, summarising and thematic synthesising, taking into account the change drivers elaborated in Section 2.2. These competencies are interrelated and complement each other. For example, the technology-IT competencies would enable logistics managers to better deploy their core and specialist competencies in the technologically embedded supply chain. Meanwhile, the core and specialist competencies would provide inputs for further update of the technology-IT competencies of logistics managers in the constantly evolving business environment.
3. Methodology
3.1 The survey research design
Given the nature of this research, the survey research design was adopted. Survey research, defined as “the collection of information from a sample of individuals through their responses to questions” (Check and Schutt, 2012, p. 160), is a well-established research method in many disciplines. Survey research is a useful and legitimate approach to research that has clear benefits in helping to describe and/or predict some phenomenon and their relationships (Zikmund et al., 2013). Since this research aims to explore and describe the supply chain competence profile of logistics managers in the new era, survey research is therefore appropriate.
3.2 Sampling
This study was conducted in the context of Vietnam, a developing country in which the importance of logistics has gained significant attention in recent years. Located in the Indochina peninsular in Southeast Asia and bordering the South China Sea, the S-shaped, long but narrow terrain of Vietnam has always highlighted the importance of logistics management in the country. According to the Vietnam Logistics Business Association (VLA), the industry has grown 14–16% annually in recent years, one of the fastest growing economic sectors in the country, and with a compound annual growth rate (CAGR) of 15–20% expected in the next five years (Kokalari, 2023). In terms of LPI, Vietnam was ranked 39th in 2018, which is considered an improvement compared to the country’s 53rd position in 2012, 48th in 2014 and 64th in 2016. However, the country’s LPI position slipped four places in 2023 and landed at the 43rd position (The World Bank, 2023b). According to the VLA, this is due to the decline in the scores related to timeliness, logistics competence, and tracking and tracing (Vietnamnet, 2023). Appendices 1 and 2 provide a snapshot of the LPI and logistics competence ranks of Vietnam and some other ASEAN countries.
It is apparent that logistics competence, which assesses a country’s ability to provide quality logistics services, including logistics expertise, competence of logistics operators and the availability of logistics service providers (The World Bank, 2023c), is strongly associated with the LPI of the country. In the case of Vietnam, it can be seen that the country is in the top five in the ASEAN region, but its LPI and logistics competence ranks are not that stable compared to others in the region, i.e. Singapore and the Philippines whose ranks have been consistently improved. According to the Vietnam Logistics Report 2022 (VALOMA, 2023), there are currently more than 30,000 Vietnamese logistics firms in the country, but more than 97% are micro-, small- and medium-sized enterprises which only account for about 30% of the market share. Therefore, developing and sustaining the supply chain competence of logistics managers is recognised as one of the key factors in improving the competitiveness and business performance of logistics service providers in the country. Given the growth potential of the logistics industry, and the role of logistics managers in the industry, Vietnam is therefore a good research context for logistics managers’ supply chain managerial competence to be explored.
This study examines the supply chain competence profile of logistics managers in the new era, taking into account the change drivers. For this purpose, the scope of this study was limited to logistics and related business areas which were classified in Section H – Transportation and Storage – of the Vietnamese economic sector system specified in the Prime Minister’s Decree No. 27/2018/QD-TTg (Minister of Planning and Investment, 2018). Section H is the only sector that includes business entities in the logistics domain as officially defined in this decree in the context of Vietnam. The sector includes five groups of businesses: Land transport and transport via railways and via pipelines, Water transport, Air transport, Warehousing and support activities for transportation, and Postal and courier activities. Currently, there is no universal directory in Vietnam which includes all firms registered in these five business groups under Section H as they are scattered in various directories due to limitations in the current Vietnamese statistical system. In this study, the target respondents were owners or managers of Vietnamese firms whose business is in the logistics and related business areas. The selection criteria are that they: (1) work in selected businesses, (2) are full-time equivalent employees and (3) hold top- or mid-managerial positions.
3.3 Data collection and analysis
A survey questionnaire was initially designed in English and consists of five main sections. The first section seeks various information for classification, i.e. firm type, business sector, firm size and respondents’ demographics questions. The subsequent four sections deal with four groups of logistics managers’ supply chain competence, i.e. foundational competencies, core competencies, specialist competencies and technology-IT competencies. In each of these groups, respondents are asked to rate the level of importance and their current level of expertise/possession of these competencies on the five-point categorical scales, with 1 denoting not at all important/very low, and 5 equating extremely important/very high. Following the forward-backward translation procedure for cross-cultural research suggested by Brislin (1970), it was first translated into Vietnamese by the researchers, who are fluent in both English and Vietnamese and have some industry experience in the logistics industry. The questionnaire was then back-translated into English by a language professional, and this English version was compared with the originally designed English version for any syntax discrepancies or errors. Upon the researchers’ satisfaction that both English versions are consistent, the Vietnamese version of the questionnaire was administered to the potential respondents.
An independent research company, InfoQ by GMO, with Big Data source (updated since 2012) was employed to determine and engage potential respondents. Their online networking community with vast membership rolls was used to build the sampling frame of this research. Members were required to verify and update annually their personal and company information (e.g. company name, business email address, and domain) to ensure respondents’ authenticity. A scanning process was conducted based on potential respondents’ pre-conditions such as occupation, position and industry to filter out those who did not meet the selection criteria. This data collection strategy offered several advantages, including the quickness of recruitment, ease of access to the data source and the likelihood of obtaining a range of participants from the entire country.
Prior to the survey, all prospective participants were required to express their consent to voluntary participation. Throughout the survey, the participants’ responses were maintained in a completely anonymous manner, ensuring the confidentiality of their personal information. The questionnaires were distributed via an online survey platform with 481 invitations sent out to those eligible firms registered in the database of the independent research company, InfoQ by GMO. This process led to 342 respondents providing their willingness to participate in the online survey, representing 71.1% response rate. Upon examining the validation of responses, 43 incomplete answers and 30 responses from individuals who did not meet the selection criteria (e.g. working in different industries or holding different job positions) were excluded from the dataset. Subsequently, the remaining 269 valid responses were utilised for data analysis. A common method bias test using Harman’s single-factor analysis (Podsakoff et al., 2012) was conducted on 38 competencies for both data related to perceived importance and current level of possession. The results revealed that the leading factor accounted for 19.97% (importance) and 40.99% (possession), indicating that common method bias does not seem to be an issue in this study.
As this research explores the nexus between expectation and possession of logistics managers’ supply chain managerial competence in the new era, the analyses of differences between the perceived importance and current level of possession of competency groups, illustrated in radar graphs, were conducted, apart from descriptive analyses of the mean scores of perceived importance and possession levels of these competencies. These tools help to highlight not only the ranking of these competencies in terms of perceived importance and possession level but also the nexus between them. Based on these analyses, an importance-possession matrix of competency development was also plotted for strategy formulation accordingly.
4. Findings
4.1 Respondents’ demographic information
Table 2 shows the demographic profile of respondents, all of whom are at middle-management level or above. Most respondents have working experience ranging from 6 to 10 years, followed by those who have worked from 2 to 5 years and 11–20 years. Regarding educational qualification, most respondents have a bachelor and master degrees. In terms of firm types, limited liability and stock holding firms are predominant. Regarding firm size, most firms in the survey have between 51 and 100 employees. Given the abovementioned demographic information, it can be seen that respondents in this survey are qualified to provide their professional opinion on the main research questions in this study.
4.2 The perceived importance of logistics managers’ supply chain competence
In this research, the profile of logistics managers’ supply chain competence is attributed by four groups of competencies, i.e. foundational, core, specialist and technology-IT. Respondents were asked to rate the perceived importance of these competencies to their individual performance. Appendix 3 presents the descriptive statistics results of the perceived importance of logistics managers’ supply chain competence in all competency groups.
It can be seen from Appendix 3 that respondents perceived all competencies in the four groups as important to their individual performance in their job. Notably, the top three most important competencies in each group that would contribute to the individual performance of logistics managers are as follows:
Adaptability, judgement and decision making and resilient mindset (Foundation group)
Supply chain dynamics, supply chain design and supply chain resilience (Core group)
Order management and customer service, packaging management and procurement strategy and management (Specialist group)
Data analytics/data processing, computational competency and optimisation and simulation ability (Technology-IT group)
An ANOVA test with Tukey HSD comparisons was conducted on all competencies, and it was revealed that although the top three competencies are not statistically different from each other in terms of their perceived importance, such a significant difference exists between them and those in the latter half of the ranking table.
Table 3 illustrates the perceived importance of logistics managers’ supply chain competence at the group level. In this connection, respondents perceived the foundation competency group as the most important to their individual performance, followed by technology-IT, then core and specialist competency groups. An ANOVA test with Tukey HSD comparisons was also conducted on all competency groups, and the results (Table 4) indicated that there is a statistically significant difference between the foundation competency group and the others, in which the former was perceived as significantly more important than the latter.
Perceived importance of logistics managers’ competence at the group level
| Competency groups | Mean | Standard deviation |
|---|---|---|
| Foundation competencies (FC) | 4.48 | 0.25 |
| Technology-IT competencies (TC) | 4.06 | 0.58 |
| Core competencies (CC) | 4.05 | 0.45 |
| Specialist competencies (SC) | 3.98 | 0.39 |
| Competency groups | Mean | Standard deviation |
|---|---|---|
| Foundation competencies (FC) | 4.48 | 0.25 |
| Technology-IT competencies (TC) | 4.06 | 0.58 |
| Core competencies (CC) | 4.05 | 0.45 |
| Specialist competencies (SC) | 3.98 | 0.39 |
Note(s): 1 = Not at all important, 5 = Extremely important
Source(s): Authors’ own work
Comparison of perceived importance between competency groups
| Between-group multiple comparisons | ||||||
|---|---|---|---|---|---|---|
| Dependent variable | ||||||
| Tukey HSD | ||||||
| (I) Competencies | Mean difference (I-J) | Std. error | Sig | 95% confidence interval | ||
| Lower bound | Upper bound | |||||
| FC | CC | 0.436* | 0.037 | 0.000 | 0.340 | 0.532 |
| SC | 0.507* | 0.037 | 0.000 | 0.411 | 0.603 | |
| TC | 0.418* | 0.037 | 0.000 | 0.322 | 0.514 | |
| CC | FC | −0.436* | 0.0373 | 0.000 | −0.532 | −0.340 |
| SC | 0.071 | 0.037 | 0.232 | −0.025 | 0.167 | |
| TC | −0.017 | 0.037 | 0.966 | −0.113 | 0.079 | |
| SC | FC | −0.507* | 0.037 | 0.000 | −0.603 | −0.411 |
| CC | −0.071 | 0.037 | 0.232 | −0.167 | 0.025 | |
| TC | −0.089 | 0.037 | 0.086 | −0.184 | 0.008 | |
| TC | FC | −0.418* | 0.037 | 0.000 | −0.514 | −0.322 |
| CC | 0.017 | 0.037 | 0.966 | −0.079 | 0.113 | |
| SC | 0.089 | 0.037 | 0.086 | −0.008 | 0.184 | |
| Between-group multiple comparisons | ||||||
|---|---|---|---|---|---|---|
| Dependent variable | ||||||
| Tukey HSD | ||||||
| (I) Competencies | Mean difference (I-J) | Std. error | Sig | 95% confidence interval | ||
| Lower bound | Upper bound | |||||
| FC | CC | 0.436* | 0.037 | 0.000 | 0.340 | 0.532 |
| SC | 0.507* | 0.037 | 0.000 | 0.411 | 0.603 | |
| TC | 0.418* | 0.037 | 0.000 | 0.322 | 0.514 | |
| CC | FC | −0.436* | 0.0373 | 0.000 | −0.532 | −0.340 |
| SC | 0.071 | 0.037 | 0.232 | −0.025 | 0.167 | |
| TC | −0.017 | 0.037 | 0.966 | −0.113 | 0.079 | |
| SC | FC | −0.507* | 0.037 | 0.000 | −0.603 | −0.411 |
| CC | −0.071 | 0.037 | 0.232 | −0.167 | 0.025 | |
| TC | −0.089 | 0.037 | 0.086 | −0.184 | 0.008 | |
| TC | FC | −0.418* | 0.037 | 0.000 | −0.514 | −0.322 |
| CC | 0.017 | 0.037 | 0.966 | −0.079 | 0.113 | |
| SC | 0.089 | 0.037 | 0.086 | −0.008 | 0.184 | |
Note(s): *The mean difference is significant at the 0.05 level
Source(s): Authors’ own work
Overall, the empirical validation confirms the proposed logistics managers’ supply chain competence framework with all competencies perceived as important to the individual performance of logistics managers in the new era with some new insights. Specifically, some competencies related to supply chain resilience and technology are highly regarded among the most important ones. This supports the contingency approach to competency development advocated in this research, as they were derived from key change drivers, e.g. Industry 4.0, and post-COVID-19 VUCA (volatility, uncertainty, complexity and ambiguity) business environment.
4.3 The current level of possession of logistics managers’ supply chain competence
Apart from indicating the perceived importance of competencies contributing to logistics managers’ individual performance, respondents were also asked to rate their current level of possession of these competencies. The descriptive statistics results of logistics managers’ current level of possession of competence in all competency groups are summarised in Appendix 4.
Results from Appendix 4 indicate that the top three competencies for which respondents currently have the highest level of possession in each group are:
Growth mindset, systems thinking and leadership and emotional intelligence (Foundation group)
Supply chain dynamics, supply chain resilience and supply chain design (Core group)
Packaging management, procurement strategy and management and returns management (Specialist group)
Computational competency, data analytics/data processing and optimisation and simulation ability (Technology-IT group)
An ANOVA test with Tukey HSD comparisons was performed on all competencies regarding their current level of possession, and it was revealed that although the top three competencies are not statistically different from each other, there is a statistically significant difference between them and those in the latter half of the ranking table.
Meanwhile, at the group level, it can be seen from Table 5 that the competency group in which respondents currently possess the highest level is foundation, followed by technology-IT, core and then specialist competency groups. This takes the same pattern as the perceived importance of these groups. Overall, respondents currently possess all competencies and groups at above average and high levels. Similarly, an ANOVA test with Tukey HSD comparisons was also conducted on all competency groups, and the results (Table 6) indicated that the level of possession in the foundation competency group is higher (with statistical significance) than that of three other groups. Meanwhile, such a statistical difference also exists between the technology-IT and specialist competency groups, in that the level of possession in the latter is significantly less than that in the former.
Current possession of logistics managers’ competence at the group level
| Competency groups | Mean | Standard deviation |
|---|---|---|
| Foundation competencies (FC) | 4.29 | 0.51 |
| Technology-IT competencies (TC) | 4.03 | 0.61 |
| Core competencies (CC) | 3.93 | 0.47 |
| Specialist competencies (SC) | 3.89 | 0.49 |
| Competency groups | Mean | Standard deviation |
|---|---|---|
| Foundation competencies (FC) | 4.29 | 0.51 |
| Technology-IT competencies (TC) | 4.03 | 0.61 |
| Core competencies (CC) | 3.93 | 0.47 |
| Specialist competencies (SC) | 3.89 | 0.49 |
Note(s): 1 = Very low, 5 = Very high
Source(s): Authors’ own work
Comparison of current level of possession between competency groups
| Between-group multiple comparisons | ||||||
|---|---|---|---|---|---|---|
| Dependent variable | ||||||
| Tukey HSD | ||||||
| (I) Competencies | Mean difference (I-J) | Std. error | Sig | 95% confidence interval | ||
| Lower bound | Upper bound | |||||
| FC | CC | 0.358* | 0.045 | 0.000 | 0.242 | 0.474 |
| SC | 0.392* | 0.045 | 0.000 | 0.276 | 0.509 | |
| TC | 0.257* | 0.045 | 0.000 | 0.140 | 0.373 | |
| CC | FC | −0.358* | 0.045 | 0.000 | −0.474 | −0.242 |
| SC | 0.034 | 0.045 | 0.872 | −0.082 | 0.151 | |
| TC | −0.101 | 0.045 | 0.112 | −0.218 | 0.015 | |
| SC | FC | −0.392* | 0.045 | 0.000 | −0.509 | −0.276 |
| CC | −0.034 | 0.045 | 0.872 | −0.151 | 0.082 | |
| TC | −0.136* | 0.045 | 0.014 | −0.252 | −0.019 | |
| TC | FC | −0.257* | 0.045 | 0.000 | −0.373 | −0.140 |
| CC | 0.101 | 0.045 | 0.112 | −0.015 | 0.218 | |
| SC | 0.136* | 0.045 | 0.014 | 0.019 | 0.252 | |
| Between-group multiple comparisons | ||||||
|---|---|---|---|---|---|---|
| Dependent variable | ||||||
| Tukey HSD | ||||||
| (I) Competencies | Mean difference (I-J) | Std. error | Sig | 95% confidence interval | ||
| Lower bound | Upper bound | |||||
| FC | CC | 0.358* | 0.045 | 0.000 | 0.242 | 0.474 |
| SC | 0.392* | 0.045 | 0.000 | 0.276 | 0.509 | |
| TC | 0.257* | 0.045 | 0.000 | 0.140 | 0.373 | |
| CC | FC | −0.358* | 0.045 | 0.000 | −0.474 | −0.242 |
| SC | 0.034 | 0.045 | 0.872 | −0.082 | 0.151 | |
| TC | −0.101 | 0.045 | 0.112 | −0.218 | 0.015 | |
| SC | FC | −0.392* | 0.045 | 0.000 | −0.509 | −0.276 |
| CC | −0.034 | 0.045 | 0.872 | −0.151 | 0.082 | |
| TC | −0.136* | 0.045 | 0.014 | −0.252 | −0.019 | |
| TC | FC | −0.257* | 0.045 | 0.000 | −0.373 | −0.140 |
| CC | 0.101 | 0.045 | 0.112 | −0.015 | 0.218 | |
| SC | 0.136* | 0.045 | 0.014 | 0.019 | 0.252 | |
Note(s): *The mean difference is significant at the 0.05 level
Source(s): Authors’ own work
4.4 The nexus of logistics managers’ supply chain competence expectation and possession
To shed more light on the nexus between the expectation, reflected by the perceived importance and the current level of possession, of logistics managers’ supply chain competence profile, a gap analysis was conducted accordingly. In this connection, a paired samples t-test on four competency groups (i.e. foundation, core, specialist and technology-IT competencies) was performed by comparing the overall mean scores of perceived importance with the actual possession levels. Table 7 indicates that the actual possession levels of competencies are significantly lower than their perceived importance, with statistically significant competency gaps at the 5% level. The highest gap score is with the foundation competency group, followed by that of core and specialist competency groups, whereas the technology-IT group experiences the lowest difference between expectation and current level of possession.
The difference between expectation and possession of logistics managers’ supply chain competence
| Competency gap | Paired differences | t-value | |||||
|---|---|---|---|---|---|---|---|
| Mean | Standard deviation | Standard error mean | 95% confidence interval of the difference | ||||
| Lower | Upper | ||||||
| Pair 1 | FC_required – FC_actual | 0.196 | 0.472 | 0.029 | 0.140 | 0.253 | 6.821 |
| Pair 2 | CC_required – CC_actual | 0.118 | 0.242 | 0.015 | 0.089 | 0.148 | 8.036 |
| Pair 3 | SC_required – SC_actual | 0.082 | 0.259 | 0.016 | 0.051 | 0.113 | 5.209 |
| Pair 4 | TC_required – TC_actual | 0.035 | 0.228 | 0.014 | 0.007 | 0.062 | 2.486 |
| Competency gap | Paired differences | t-value | |||||
|---|---|---|---|---|---|---|---|
| Mean | Standard deviation | Standard error mean | 95% confidence interval of the difference | ||||
| Lower | Upper | ||||||
| Pair 1 | FC_required – FC_actual | 0.196 | 0.472 | 0.029 | 0.140 | 0.253 | 6.821 |
| Pair 2 | CC_required – CC_actual | 0.118 | 0.242 | 0.015 | 0.089 | 0.148 | 8.036 |
| Pair 3 | SC_required – SC_actual | 0.082 | 0.259 | 0.016 | 0.051 | 0.113 | 5.209 |
| Pair 4 | TC_required – TC_actual | 0.035 | 0.228 | 0.014 | 0.007 | 0.062 | 2.486 |
Note(s): FC_required: perceived importance of foundation competencies, CC_required: received importance of core competencies, SC_required: received importance of specialist competencies, TC_required: received importance of technology IT competencies, FC_actual: current possession of foundation competencies, CC_actual: current possession of core competencies, SC_actual: current possession of specialist competencies, TC_actual: current possession of technology IT competencies
Source(s): Authors’ own work
To further visualise the gaps between expectation and possession in all four groups of competencies, radar charts were generated, as illustrated in Figures 2–5. It can be seen that, with the exception of leadership and emotional intelligence and growth mindset, gaps exist in all competencies groups, in that the latter is less than the former, with the largest gaps displayed at the foundation and the least at the technology-IT competency groups. Specifically, the largest gaps between possession level and perceived importance exist regarding resilient mindset, teamwork mindset and judgement and decision making in the foundation competency group. In the core group, supply chain dynamics, supply chain design and supply chain orientation are competencies whose gaps are the largest. Concerning the specialist competency group, the largest gaps between perceived importance and possession level are in order management and customer service, warehousing and facilities management, and forecasting and inventory management. Meanwhile, it is also interesting to note that the largest gaps in the technology-IT group exist regarding understanding autonomous robotics applications, understanding AI and Machine Learning applications, and data analytics/data processing.
The title at the top of the radar chart is labeled “Difference between perceived importance and possession of Foundation competencies”. The radar chart displays values across fifteen categories, labeled clockwise as follows: “F C 1 - Adaptability”, “F C 4 - Collaboration and synergy”, “F C 5 - Communications”, “F C 3 - Creative thinking and innovation”, “F C 6 - Customer centricity”, “F C 11 - Digital mindset”, “F C 7 - Environmental sustainability mindset”, “F C 10 - Ethical behaviour”, “F C 15 - Growth mindset”, “F C 13 - Judgement and decision making”, “F C 2 - Leadership and emotional intelligence”, “F C 8 - Outcome-driven”, “F C 12 - Resilient mindset”, “F C 9 - Systems thinking”, and “F C 14 - Teamwork mindset”. Each category is represented by an axis radiating from the center, with concentric rings marking intervals from 3.80 to 4.70 in 0.10 unit increments. Each axis radiating from the centre shows two data lines, with the blue line representing the Level of importance, and the orange line representing the Level of possession. The data values for each category are as follows: Level of importance (blue line): F C 1 - Adaptability: 4.64. F C 4 - Collaboration and synergy: 4.33. F C 5 - Communications: 4.44. F C 3 - Creative thinking and innovation: 4.38. F C 6 - Customer centricity: 4.45. F C 11 - Digital mindset: 4.52. F C 7 - Environmental sustainability mindset: 4.41. F C 10 - Ethical behaviour: 4.55. F C 15 - Growth mindset: 4.41. F C 13 - Judgement and decision making: 4.60. F C 2 - Leadership and emotional intelligence: 4.39. F C 8 - Outcome-driven: 4.51. F C 12 - Resilient mindset: 4.57. F C 9 - Systems thinking: 4.51. F C 14 - Teamwork mindset: 4.54. Level of possession (orange line): F C 1 - Adaptability: 4.30. F C 4 - Collaboration and synergy: 4.30. F C 5 - Communications: 4.17. F C 3 - Creative thinking and innovation: 4.25. F C 6 - Customer centricity: 4.14. F C 11 - Digital mindset: 4.42. F C 7 - Environmental sustainability mindset: 4.20. F C 10 - Ethical behaviour: 4.30. F C 15 - Growth mindset: 4.48. F C 13 - Judgement and decision making: 4.25. F C 2 - Leadership and emotional intelligence: 4.43. F C 8 - Outcome-driven: 4.32. F C 12 - Resilient mindset: 4.16. F C 9 - Systems thinking: 4.43. F C 14 - Teamwork mindset: 4.14. Note: All numerical data values are approximated.Foundation competency gap
The title at the top of the radar chart is labeled “Difference between perceived importance and possession of Foundation competencies”. The radar chart displays values across fifteen categories, labeled clockwise as follows: “F C 1 - Adaptability”, “F C 4 - Collaboration and synergy”, “F C 5 - Communications”, “F C 3 - Creative thinking and innovation”, “F C 6 - Customer centricity”, “F C 11 - Digital mindset”, “F C 7 - Environmental sustainability mindset”, “F C 10 - Ethical behaviour”, “F C 15 - Growth mindset”, “F C 13 - Judgement and decision making”, “F C 2 - Leadership and emotional intelligence”, “F C 8 - Outcome-driven”, “F C 12 - Resilient mindset”, “F C 9 - Systems thinking”, and “F C 14 - Teamwork mindset”. Each category is represented by an axis radiating from the center, with concentric rings marking intervals from 3.80 to 4.70 in 0.10 unit increments. Each axis radiating from the centre shows two data lines, with the blue line representing the Level of importance, and the orange line representing the Level of possession. The data values for each category are as follows: Level of importance (blue line): F C 1 - Adaptability: 4.64. F C 4 - Collaboration and synergy: 4.33. F C 5 - Communications: 4.44. F C 3 - Creative thinking and innovation: 4.38. F C 6 - Customer centricity: 4.45. F C 11 - Digital mindset: 4.52. F C 7 - Environmental sustainability mindset: 4.41. F C 10 - Ethical behaviour: 4.55. F C 15 - Growth mindset: 4.41. F C 13 - Judgement and decision making: 4.60. F C 2 - Leadership and emotional intelligence: 4.39. F C 8 - Outcome-driven: 4.51. F C 12 - Resilient mindset: 4.57. F C 9 - Systems thinking: 4.51. F C 14 - Teamwork mindset: 4.54. Level of possession (orange line): F C 1 - Adaptability: 4.30. F C 4 - Collaboration and synergy: 4.30. F C 5 - Communications: 4.17. F C 3 - Creative thinking and innovation: 4.25. F C 6 - Customer centricity: 4.14. F C 11 - Digital mindset: 4.42. F C 7 - Environmental sustainability mindset: 4.20. F C 10 - Ethical behaviour: 4.30. F C 15 - Growth mindset: 4.48. F C 13 - Judgement and decision making: 4.25. F C 2 - Leadership and emotional intelligence: 4.43. F C 8 - Outcome-driven: 4.32. F C 12 - Resilient mindset: 4.16. F C 9 - Systems thinking: 4.43. F C 14 - Teamwork mindset: 4.14. Note: All numerical data values are approximated.Foundation competency gap
The title at the top of the radar chart is labeled “Difference between perceived importance and possession of Core competencies.” The radar chart displays values across eight categories, labeled clockwise as follows: “C C 5 - Supply chain dynamics”, “C C 3 - Supply chain design”, “C C 6 - Supply chain resilience”, “C C 7 - Logistics-transport regulations”, “C C 4 - Supply chain and logistics analytics”, “C C 1 - Supply chain orientation”, “C C 2 - Supply chain strategy”, and “C C 8 - Reverse supply chain”. Each category is represented by an axis radiating from the center of the chart, with nine concentric pentagonal rings indicating value intervals from 3.40 to 4.30 in 0.10 unit increments. Each axis radiating from the center shows two data lines, with the blue line representing the Level of importance and the orange line representing the Level of possession. The data values for each category are as follows: Level of importance (blue line): C C 5 - Supply chain dynamics: 4.28. C C 3 - Supply chain design: 4.23. C C 6 - Supply chain resilience: 4.23. C C 7 - Logistics-transport regulations: 4.05. C C 4 - Supply chain and logistics analytics: 3.99. C C 1 - Supply chain orientation: 3.88. C C 2 - Supply chain strategy: 3.86. C C 8 - Reverse supply chain: 3.84. Level of possession (orange line): C C 5 - Supply chain dynamics: 4.12. C C 3 - Supply chain design: 4.08. C C 6 - Supply chain resilience: 4.10. C C 7 - Logistics-transport regulations: 3.91. C C 4 - Supply chain and logistics analytics: 3.92. C C 1 - Supply chain orientation: 3.74. C C 2 - Supply chain strategy: 3.71. C C 8 - Reverse supply chain: 3.84. Note: All numerical data values are approximated.Core competency gap
The title at the top of the radar chart is labeled “Difference between perceived importance and possession of Core competencies.” The radar chart displays values across eight categories, labeled clockwise as follows: “C C 5 - Supply chain dynamics”, “C C 3 - Supply chain design”, “C C 6 - Supply chain resilience”, “C C 7 - Logistics-transport regulations”, “C C 4 - Supply chain and logistics analytics”, “C C 1 - Supply chain orientation”, “C C 2 - Supply chain strategy”, and “C C 8 - Reverse supply chain”. Each category is represented by an axis radiating from the center of the chart, with nine concentric pentagonal rings indicating value intervals from 3.40 to 4.30 in 0.10 unit increments. Each axis radiating from the center shows two data lines, with the blue line representing the Level of importance and the orange line representing the Level of possession. The data values for each category are as follows: Level of importance (blue line): C C 5 - Supply chain dynamics: 4.28. C C 3 - Supply chain design: 4.23. C C 6 - Supply chain resilience: 4.23. C C 7 - Logistics-transport regulations: 4.05. C C 4 - Supply chain and logistics analytics: 3.99. C C 1 - Supply chain orientation: 3.88. C C 2 - Supply chain strategy: 3.86. C C 8 - Reverse supply chain: 3.84. Level of possession (orange line): C C 5 - Supply chain dynamics: 4.12. C C 3 - Supply chain design: 4.08. C C 6 - Supply chain resilience: 4.10. C C 7 - Logistics-transport regulations: 3.91. C C 4 - Supply chain and logistics analytics: 3.92. C C 1 - Supply chain orientation: 3.74. C C 2 - Supply chain strategy: 3.71. C C 8 - Reverse supply chain: 3.84. Note: All numerical data values are approximated.Core competency gap
The title at the top of the radar chart is labeled “Difference between perceived importance and possession of Specialist competencies”. The radar chart displays values across eight categories, labeled clockwise as follows: “S C 6 - Order management and customer service”, “S C 7 - Packaging management”, “S C 5 - Procurement strategy and management”, “S C 4 - Operations planning and execution”, “S C 3 - Forecasting and inventory management”, “S C 1 - Transportation and distribution”, “S C 2 - Warehousing and facilities management”, and “S C 8 - Returns management”. Each category is represented by an axis radiating from the centre of the chart, with seven concentric pentagonal rings indicating value intervals from 3.60 to 4.20 in 0.10 unit increments. Each axis radiating from the centre shows two data lines, with the blue line representing the Level of importance, and the orange line representing the Level of possession. The data values for each category are as follows: Level of importance (blue line): S C 6 - Order management and customer service: 4.15. S C 7 - Packaging management: 4.05. S C 5 - Procurement strategy and management: 3.98. S C 4 - Operations planning and execution: 3.96. S C 3 - Forecasting and inventory management: 3.95. S C 1 - Transportation and distribution: 3.92. S C 2 - Warehousing and facilities management: 3.91. S C 8 - Returns management: 3.90. Level of possession (orange line): S C 6 - Order management and customer service: 3.84. S C 7 - Packaging management: 4.00. S C 5 - Procurement strategy and management: 3.94. S C 4 - Operations planning and execution: 3.89. S C 3 - Forecasting and inventory management: 3.89. S C 1 - Transportation and distribution: 3.87. S C 2 - Warehousing and facilities management: 3.84. S C 8 - Returns management: 3.90. Note: All numerical data values are approximated.Specialist competency gap
The title at the top of the radar chart is labeled “Difference between perceived importance and possession of Specialist competencies”. The radar chart displays values across eight categories, labeled clockwise as follows: “S C 6 - Order management and customer service”, “S C 7 - Packaging management”, “S C 5 - Procurement strategy and management”, “S C 4 - Operations planning and execution”, “S C 3 - Forecasting and inventory management”, “S C 1 - Transportation and distribution”, “S C 2 - Warehousing and facilities management”, and “S C 8 - Returns management”. Each category is represented by an axis radiating from the centre of the chart, with seven concentric pentagonal rings indicating value intervals from 3.60 to 4.20 in 0.10 unit increments. Each axis radiating from the centre shows two data lines, with the blue line representing the Level of importance, and the orange line representing the Level of possession. The data values for each category are as follows: Level of importance (blue line): S C 6 - Order management and customer service: 4.15. S C 7 - Packaging management: 4.05. S C 5 - Procurement strategy and management: 3.98. S C 4 - Operations planning and execution: 3.96. S C 3 - Forecasting and inventory management: 3.95. S C 1 - Transportation and distribution: 3.92. S C 2 - Warehousing and facilities management: 3.91. S C 8 - Returns management: 3.90. Level of possession (orange line): S C 6 - Order management and customer service: 3.84. S C 7 - Packaging management: 4.00. S C 5 - Procurement strategy and management: 3.94. S C 4 - Operations planning and execution: 3.89. S C 3 - Forecasting and inventory management: 3.89. S C 1 - Transportation and distribution: 3.87. S C 2 - Warehousing and facilities management: 3.84. S C 8 - Returns management: 3.90. Note: All numerical data values are approximated.Specialist competency gap
The title at the top of the radar chart is labeled “Difference between perceived importance and possession of Technology - I T competencies”. The radar chart displays values across seven categories, labeled clockwise as follows: “T C 2 - Data analytics or data processing”, “T C 4 - Computational competency”, “T C 3 - Optimisation and simulation ability”, “T C 1 - Digital awareness and orientation”, “T C 6 - Ability with autonomous robots”, “T C 5 - A I and machine learning”, and “T C 7 - Ability with Internet of Things”. Each category is represented by an axis radiating from the centre of the chart, with seven concentric pentagonal rings indicating value intervals from 3.70 to 4.30 in 0.10 unit increments. Each axis radiating from the centre shows two data lines, with the blue line representing the Level of importance, and the orange line representing the Level of possession. The data values for each category are as follows: Level of importance (blue line): T C 2 - Data analytics or data processing: 4.25. T C 4 - Computational competency: 4.23. T C 3 - Optimisation and simulation ability: 4.05. T C 1 - Digital awareness and orientation: 4.02. T C 6 - Ability with autonomous robots: 4.00. T C 5 - A I and machine learning: 3.97. T C 7 - Ability with Internet of Things: 3.94. Level of possession (orange line): T C 2 - Data analytics or data processing: 4.21. T C 4 - Computational competency: 4.21. T C 3 - Optimisation and simulation ability: 4.02. T C 1 - Digital awareness and orientation: 3.99. T C 6 - Ability with autonomous robots: 3.94. T C 5 - A I and machine learning: 3.93. T C 7 - Ability with Internet of Things: 3.92. Note: All numerical data values are approximated.Technology-IT competency gap
The title at the top of the radar chart is labeled “Difference between perceived importance and possession of Technology - I T competencies”. The radar chart displays values across seven categories, labeled clockwise as follows: “T C 2 - Data analytics or data processing”, “T C 4 - Computational competency”, “T C 3 - Optimisation and simulation ability”, “T C 1 - Digital awareness and orientation”, “T C 6 - Ability with autonomous robots”, “T C 5 - A I and machine learning”, and “T C 7 - Ability with Internet of Things”. Each category is represented by an axis radiating from the centre of the chart, with seven concentric pentagonal rings indicating value intervals from 3.70 to 4.30 in 0.10 unit increments. Each axis radiating from the centre shows two data lines, with the blue line representing the Level of importance, and the orange line representing the Level of possession. The data values for each category are as follows: Level of importance (blue line): T C 2 - Data analytics or data processing: 4.25. T C 4 - Computational competency: 4.23. T C 3 - Optimisation and simulation ability: 4.05. T C 1 - Digital awareness and orientation: 4.02. T C 6 - Ability with autonomous robots: 4.00. T C 5 - A I and machine learning: 3.97. T C 7 - Ability with Internet of Things: 3.94. Level of possession (orange line): T C 2 - Data analytics or data processing: 4.21. T C 4 - Computational competency: 4.21. T C 3 - Optimisation and simulation ability: 4.02. T C 1 - Digital awareness and orientation: 3.99. T C 6 - Ability with autonomous robots: 3.94. T C 5 - A I and machine learning: 3.93. T C 7 - Ability with Internet of Things: 3.92. Note: All numerical data values are approximated.Technology-IT competency gap
5. Discussion
The aforesaid analysis of empirical data derives several important points of discussion. First, it is confirmed that all competencies in the proposed framework of logistics managers’ supply chain competence are valid and important in contributing to their individual performance with some new insights. Leveraged on previous models and frameworks, the competency framework proposed in this research consists of not only key elements synthesised from the literature but also those derived from the evolving business environment influenced by the change drivers, such as Industry 4.0, the COVID-19 pandemic, sustainability, responsiveness and customer centrism focus – which are new in this research. In this connection, “resilient mindset” and “digital mindset” in the foundation group, “supply chain resilience” in the core group, and many competencies in the newly proposed technology-IT group, e.g. “data analytics/data processing”, “optimisation and simulation ability”, “digital awareness and orientation”, etc. were also perceived as important to the individual performance of logistics managers in the new era. The appreciation of these newly proposed competencies implies that the competency profile of logistics managers in the new era needs to go beyond traditional portfolios and encompass those that reflect contemporary requirements in the industry. Although key elements in the foundation, core and specialist competency groups remain unchanged, similar to previous studies (e.g. van Hoek et al., 2020, Mageto and Luke, 2020, Derwik and Hellström, 2017, Derwik et al., 2016), the finding regarding competencies derived from change drivers aligns well with the contingency approach proposed in this research to formulate the competency profile for logistics managers and implies that such a profile may be evolving following the contemporary change drivers. This is an important contribution as it confirms that the contingency approach should be applied in developing competency profiles in the logistics and supply chain management industry, thus expanding its application beyond other disciplines. The application of this approach contributes to enhancing knowledge in the field, as it implies that logistics managers’ competency profile is evolving and its development should always consider contingency change factors in the business environment.
Secondly, it is worth noting that the foundation, technology-IT, core and specialist competency groups were all perceived as important to the individual performance of logistics managers, and those related to contemporary change drivers are required for them to cope with new requirements in the business environment. This finding is significant as it implies a well-rounded profile to be developed for effective logistics managers. Meanwhile, the foundation competency group was rated as more important to the individual performance of logistics managers than others, which align with several earlier research, e.g. Murphy and Poist (1991a, b, 2006, 2007), Thai et al. (2011, 2012), Thai (2012). Regardless of the time, this important finding implies that “soft competencies” such as those in the foundation/management group are transferrable across professions and form the solid background of logistics managers’ supply chain competence in the new era. Essentially, while the role of contemporary change drivers-related competencies to individual performance is undeniable, those of foundation nature are still critical to logistics professionals at the senior level as fundamental traits of effective managers, upon which managerial tasks can be carried out successfully regardless of their specialised areas of expertise. However, this finding may be unique in the context of Vietnam, a developing country where the importance of logistics is gaining increasing attention, and differs from countries in which logistics is an established industry. For example, a recent study in the UK revealed that 3PL senior managers’ relational and behavioural skills are more important than traditional functional and managerial skills (Midgley and Bak, 2022).
Meanwhile, the disparity between the perceived importance and current level of possession of competencies in all four groups of the proposed competency framework of logistics managers also deserves managerial attention. First, while the foundation competency group was rated as more important than the others, ironically the largest gaps between possession level and perceived importance also exist in this group. It is important to note that such a gap is also evidenced in contemporary competencies such as resilient mindset, supporting the tenet that senior management needs to pay special attention to helping their firms’ logistics managers acquire foundation competencies early, including those derived from change drivers in the technology-IT group, to establish a firm ground for their competency profile. Meanwhile, existing gaps also exist in the core and specialist groups relating to supply chain and logistics fundamentals, e.g. supply chain dynamics, supply chain design, supply chain orientation, order management and customer service, warehousing and facilities management, and forecasting and inventory management. These gaps imply that a time lag exists between contemporary industry requirements and response from quality logistics education and training and that more work should be done to prepare Vietnamese logistics managers for their jobs in a country where the logistics and supply chain industry is fast growing. Some specific measures to address this include, for instance, incorporating industry requirements early in the logistics education and training curricula, by establishing industry advisory committees in which industry professionals are key members, who periodically provide inputs for quality improvements.
To elaborate on the nexus of logistics managers’ supply chain managerial competence expectation and possession, an Importance-Possession Matrix – IPM (Figure 6), adapted from the Importance-Performance Analysis – IPA (Martilla and James, 1977), was charted. In combination with gap analysis, this quadrant matrix provides better and more comprehensive results in identifying and prioritising the critical competencies. In this IPM, each competency is plotted in one of the four quadrants (2 × 2) of the matrix (i.e. Building, Growing, Redistributing Resources and Maintaining Sustainably) based on the mean score of their perceived importance and current possession level.
The figure shows a square box divided into four quadrants, formed by a vertical line intersecting a horizontal line at their midpoints. The horizontal axis at the bottom is labeled “Level of importance”, and the vertical axis on the left is labeled “Level of possession”. These intersecting lines divide the square box into four labeled sections. The horizontal axis has two markings, “Low” on the left and “High” on the right. The vertical axis has two markings, “Low” at the bottom and “High” at the top. The top-left quadrant is labeled “Redistributing resources”. It is under “Low” levels of possession and “High” level of importance. Inside this quadrant, the competencies listed are as follows: “F C 15”, “F C 2”, “F C 4”, “S C 8”, and “S C 4”. The top-right quadrant is labeled “Maintaining sustainably”. It is under “High” levels of possession and “High” levels of importance. Inside this quadrant, the competencies listed are as follows: “F C 9”, “F C 11”, “F C 8”, “F C 10”, “F C 1”, “C C 5”, “C C 6”, “C C 3”, “S C 7”, “S C 5”, “T C 4”, and “T C 2”. The bottom-left quadrant is labeled “Building”. It is under “Low” levels of possession and “Low” levels of importance. Inside this quadrant, the competencies listed are as follows: “F C 3”, “F C 7”, “F C 5”, “F C 6”, “C C 4”, “C C 8”, “C C 1”, “C C 2”, “S C 3”, “S C 1”, “S C 2”, “T C 3”, “T C 1”, “T C 6”, “T C 5”, and “T C 7”. The bottom-right quadrant is labeled “Growing”. It is under “High” levels of possession and “Low” levels of importance. Inside this quadrant, the competencies listed are as follows: “F C 13”, “F C 12”, “F C 14”, “C C 7”, and “S C 6”. At the bottom of the figure, a note reads: “Note(s): The full titles of competencies can be referred to in either Appendix 3 or Appendix 4”.Importance-possession matrix of competency development
The figure shows a square box divided into four quadrants, formed by a vertical line intersecting a horizontal line at their midpoints. The horizontal axis at the bottom is labeled “Level of importance”, and the vertical axis on the left is labeled “Level of possession”. These intersecting lines divide the square box into four labeled sections. The horizontal axis has two markings, “Low” on the left and “High” on the right. The vertical axis has two markings, “Low” at the bottom and “High” at the top. The top-left quadrant is labeled “Redistributing resources”. It is under “Low” levels of possession and “High” level of importance. Inside this quadrant, the competencies listed are as follows: “F C 15”, “F C 2”, “F C 4”, “S C 8”, and “S C 4”. The top-right quadrant is labeled “Maintaining sustainably”. It is under “High” levels of possession and “High” levels of importance. Inside this quadrant, the competencies listed are as follows: “F C 9”, “F C 11”, “F C 8”, “F C 10”, “F C 1”, “C C 5”, “C C 6”, “C C 3”, “S C 7”, “S C 5”, “T C 4”, and “T C 2”. The bottom-left quadrant is labeled “Building”. It is under “Low” levels of possession and “Low” levels of importance. Inside this quadrant, the competencies listed are as follows: “F C 3”, “F C 7”, “F C 5”, “F C 6”, “C C 4”, “C C 8”, “C C 1”, “C C 2”, “S C 3”, “S C 1”, “S C 2”, “T C 3”, “T C 1”, “T C 6”, “T C 5”, and “T C 7”. The bottom-right quadrant is labeled “Growing”. It is under “High” levels of possession and “Low” levels of importance. Inside this quadrant, the competencies listed are as follows: “F C 13”, “F C 12”, “F C 14”, “C C 7”, and “S C 6”. At the bottom of the figure, a note reads: “Note(s): The full titles of competencies can be referred to in either Appendix 3 or Appendix 4”.Importance-possession matrix of competency development
Competencies which were perceived at a low-to-medium level of both expectation and possession would fall in the Building quadrant, which implies that firms would need to focus on building these competencies for their logistics managers to establish a solid foundation for their competency profile. In this study, four foundation, four core, three specialist and four technology-IT competencies fall in this quadrant, which account for nearly half (16) of the total number of competencies. In contrast, the Maintaining Sustainably quadrant presents 12 competencies that were evaluated medium-to-high in both expectation and possession, with five of them being foundation, three being core, two being specialist and two being technology-IT competencies. Since competencies in this quadrant can contribute significantly to the individual performance of logistics managers and, subsequently, their firm performance, they should be maintained sustainably in the long run through continual education and training, as well as other human resource retaining programs. As shown in Figure 6, most of the competencies (28 out of 38) fall in these two opposite quadrants, which demonstrates a significant distinction among competencies acquired by Vietnamese logistics managers.
The aforesaid realisation presents thought-provoking implications for logistics education and training in Vietnam. First, although there are 12 competencies in the Maintaining Sustainably quadrant across four groups of competencies, only a few of them (i.e. digital mindset, supply chain resilience, data analytics/data processing) are related to contemporary change drivers. What this means for the senior management of firms which participated in this research is that strategies are to be put in place to enhance the possession of important competencies, especially those required by the contemporary business environment, among their logistics managers. In this connection, various forms of training both within and outside the organisation should be conducted to help logistics managers acquire essential competencies for keeping up with what are contemporarily required for their successful performance, especially in Vietnam where sustainable development and digital transformation are gaining speed. Meanwhile, the fact that nearly half of competencies are currently positioned in the Building quadrant including those derived from the contemporary change drivers across the four competency groups apart from those adopted in the literature also indicates that the competency profile of Vietnamese logistics managers in this study is still at the early stage of development, and further work is needed.
There are five competencies (three foundation, one core and one specialist competencies) which fall in the Growing quadrant, and deserve a greater degree of concentration since they were perceived medium-to-high in terms of importance to logistics managers’ individual performance but rated low-to-medium level of possession. This implies that firms will need to implement prioritised improvements to enhance the possession of these competencies for their logistics managers through education, training and human resource development programs, both internally and externally. The last quadrant, Redistributing Resources, includes five foundation and two specialist competencies that were evaluated as having medium-to-high level of possession while perceived as of low-to-medium level of importance. Therefore, it would be prudent to redistribute excessive resources, in terms of education and training, towards other competencies that have the potential to enhance and sustain the individual performance of logistics managers and their competitiveness, such as those in the Maintaining Sustainably and Growing quadrants. In the long run, the key objective of competency development is that each of the competencies in the profile of logistics managers shall evolve to become an element in the Maintaining Sustainably quadrant of the IPM which together contribute to enhancing logistics managers’ individual performance and their competitiveness.
6. Conclusion
Although there has been some research on what the competency profile of logistics managers should entail over the past decades, it can be argued that such a profile is contingent on the evolution of many change drivers. In this research, the supply chain managerial competence profile of logistics managers in the new era is formulated by synthesising existing models and frameworks, and taking into account contemporary change drivers, i.e. Industry 4.0, the COVID-19 pandemic, as well as rising requirements for sustainability, responsiveness and customer centrism. It was found that the proposed profile of four groups and 38 competencies is valid and important to the individual performance of logistics managers in the context of Vietnam, which supports the tenet that logistics managers in the new era need to have a well-rounded profile of competencies, including those derived from contemporary change drivers. Findings also indicated that the foundation competency group was perceived as more important than others for Vietnamese logistics managers in a developing country in which the importance of logistics is gaining increasing attention, which may differ in other contexts. Besides, it was also revealed that respondents in this research currently possess those competencies at a level which is lower than their perceived importance, with the foundation competency group having the largest level of disparity. This calls for concrete actions from both the industry and education and training institutions in Vietnam to address these competency gaps.
This research induces several academic and managerial implications. Firstly, it introduces an improvised framework of logistics managers’ supply chain managerial competence adopting the contingency approach, which has been empirically validated. This contributes to expanding the body of knowledge on how the competency profile of logistics managers should be developed. Specifically, in revising existing or developing new competency profiles for logistics managers, scholars and practitioners should adopt the contingency approach in identifying contemporary change drivers and analysing what new competencies shall be derived therein. Secondly, the IPM matrix of competencies introduced in this research with the four quadrants of Building, Growing, Redistributing Resources and Maintaining Sustainably can be used as both the conceptual and managerial tool to classify and prioritise competencies for various purposes, e.g. education, training and policy implementation. In terms of managerial implications, this research provides insights into the current competency profile of logistics managers in Vietnam, which can assist senior management with human resources development in their firms. Specifically, it is essential that Vietnamese logistics firms focus on providing education and training opportunities, both internally and externally, to enhance the level of possession of all competencies whose gaps between perceived importance and possession are the largest across the groups, especially those in the Maintaining Sustainably, Growing and Building quadrants of the IPM. Specifically, apart from internal training, the senior management should consider sending their logistics managers to logistics training courses organised by various education and training institutions both in Vietnam and overseas, apart from those organised by professional peak associations such as the Vietnam Logistics Business Association. It is also imminent for logistics education and training institutions in Vietnam to collaborate closely with the industry to address competency gaps identified in this research in a systematic manner, starting with the establishment of industry advisory boards in those institutions which provide inputs for curriculum improvements. Meanwhile, from the macro-governance perspective, it is also prudent for the Vietnamese Government to establish a national skills council which oversees important tasks of skills forecasting, providing relevant information and data to institutions and industry, and coordinating academic – industry collaboration activities related to logistics competency development. Given that this is one of a few research on the competency profile of logistics managers in Vietnam, findings and suggestions from this research can be of valuable reference to Vietnamese logistics firms in enhancing their logistics managers’ individual performance which, in turn, can contribute to improving the logistics competence component of the country’s LPI.
Despite the aforesaid contributions, this research is constrained in its scope, i.e. only logistics managers in the 3PL sector were included in the sample. Given that logistics is also a critical business component in other manufacturing and service industries, the competency profile proposed in this research should also be replicated in future studies encompassing other sectors. Similar studies conducted in other contexts beyond Vietnam, e.g. developed countries would potentially yield interesting findings through comparative analyses and support the reliability and validity of this research. Such comparative analyses can examine the differences in competency profiles of logistics managers not only between 3PL and non-3PL sectors, but also between those in developing and developed countries where logistics development is at different stages. Meanwhile, further empirical research on the relationship between logistics managers’ competence and various aspects of their performance, as well as those of their firms, will enhance knowledge of competency development, especially in the VUCA business environment.
This research is funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under grant number 502.02-2020.324.
References
Further reading
Appendix 1 LPI ranks of Vietnam and selected ASEAN countries
The graph is titled “L P I Ranks of Selected A S E A N Countries” at the top. The horizontal axis represents the year and ranges from 2012 to 2023 in increments of 2 years. The vertical axis ranges from 0 to 80 in increments of 10 units. The graph shows six lines, each representing the L P I ranks of selected A S E A N countries over time. On the right side of the graph, the legend lists the countries as follows: red line labeled “Vietnam”, orange line labeled “Singapore”, gray line labeled “Thailand”, yellow line labeled “Malaysia”, blue line labeled “Indonesia”, and green line labeled “Philippines”. The “Vietnam” line starts at (2012, 53.03) and passes through the following points: (2014, 48.03), (2016, 63.82), (2018, 38.55), and ends at (2023, 43.29). The “Singapore” line starts at (2012, 1.45) and passes through the following points: (2014, 4.87), (2016, 4.87), (2018, 6.97), and ends at (2023, 1). The “Thailand” line starts at (2012, 38.03) and passes through the following points: (2014, 35.39), (2016, 45.13), (2018, 32.24), and ends at (2023, 34.08). The “Malaysia” line starts at (2012, 29.08) and passes through the following points: (2014, 25.13), (2016, 31.71), (2018, 40.92), and ends at (2023, 31). The “Indonesia” line starts at (2012, 59.08) and passes through the following points: (2014, 53.03), (2016, 62.5), (2018, 45.9), and ends at (2023, 60.9). The “Philippines” line starts at (2012, 52.24) and passes through the following points: (2014, 56.9), (2016, 71), (2018, 60), and ends at (2023, 42.7). At the bottom of the graph, the source reads: “Source(s): Compiled from The World Bank (2023 b)”. Note: All numerical data values are approximated.
The graph is titled “L P I Ranks of Selected A S E A N Countries” at the top. The horizontal axis represents the year and ranges from 2012 to 2023 in increments of 2 years. The vertical axis ranges from 0 to 80 in increments of 10 units. The graph shows six lines, each representing the L P I ranks of selected A S E A N countries over time. On the right side of the graph, the legend lists the countries as follows: red line labeled “Vietnam”, orange line labeled “Singapore”, gray line labeled “Thailand”, yellow line labeled “Malaysia”, blue line labeled “Indonesia”, and green line labeled “Philippines”. The “Vietnam” line starts at (2012, 53.03) and passes through the following points: (2014, 48.03), (2016, 63.82), (2018, 38.55), and ends at (2023, 43.29). The “Singapore” line starts at (2012, 1.45) and passes through the following points: (2014, 4.87), (2016, 4.87), (2018, 6.97), and ends at (2023, 1). The “Thailand” line starts at (2012, 38.03) and passes through the following points: (2014, 35.39), (2016, 45.13), (2018, 32.24), and ends at (2023, 34.08). The “Malaysia” line starts at (2012, 29.08) and passes through the following points: (2014, 25.13), (2016, 31.71), (2018, 40.92), and ends at (2023, 31). The “Indonesia” line starts at (2012, 59.08) and passes through the following points: (2014, 53.03), (2016, 62.5), (2018, 45.9), and ends at (2023, 60.9). The “Philippines” line starts at (2012, 52.24) and passes through the following points: (2014, 56.9), (2016, 71), (2018, 60), and ends at (2023, 42.7). At the bottom of the graph, the source reads: “Source(s): Compiled from The World Bank (2023 b)”. Note: All numerical data values are approximated.Appendix 2 Logistics competence ranks of Vietnam and selected ASEAN countries
The graph is titled “Logistics Competence Ranks of Selected A S E A N Countries” at the top. The horizontal axis represents the year and ranges from 2012 to 2023 in increments of 2 years. The vertical axis ranges from 0 to 90 in increments of 10 units. The graph shows six lines, each representing the logistics competence ranks of selected A S E A N countries over time. On the right side of the graph, the legend lists the countries as follows: red line labeled “Vietnam”, orange line labeled “Singapore”, gray line labeled “Thailand”, yellow line labeled “Malaysia”, blue line labeled “Indonesia”, and green line labeled “Philippines”. The “Vietnam” line starts at (2012, 82.5) and passes through the following points: (2014, 49.5), (2016, 62.3), (2018, 32.19), and ends at (2023, 53.3). The “Singapore” line starts at (2012, 6.25) and passes through the following points: (2014, 8.17), (2016, 5.28), (2018, 2.72), and ends at (2023, 1.4). The “Thailand” line starts at (2012, 49.48) and passes through the following points: (2014, 98.9), (2016, 49.48), (2018, 32.19), and ends at (2023, 38.27). The “Malaysia” line starts at (2012, 30) and passes through the following points: (2014, 32), (2016, 35.07), (2018, 35.3), and ends at (2023, 27.38). The “Indonesia” line starts at (2012, 62.3) and passes through the following points: (2014, 41.1), (2016, 55.2), (2018, 44.04), and ends at (2023, 65.18). The “Philippines” line starts at (2012, 39.2) and passes through the following points: (2014, 61), (2016, 76.7), (2018, 69.6), and ends at (2023, 46.6). At the bottom of the graph, the source reads: “Source(s): Compiled from The World Bank (2023 b)”. Note: All numerical data values are approximated.
The graph is titled “Logistics Competence Ranks of Selected A S E A N Countries” at the top. The horizontal axis represents the year and ranges from 2012 to 2023 in increments of 2 years. The vertical axis ranges from 0 to 90 in increments of 10 units. The graph shows six lines, each representing the logistics competence ranks of selected A S E A N countries over time. On the right side of the graph, the legend lists the countries as follows: red line labeled “Vietnam”, orange line labeled “Singapore”, gray line labeled “Thailand”, yellow line labeled “Malaysia”, blue line labeled “Indonesia”, and green line labeled “Philippines”. The “Vietnam” line starts at (2012, 82.5) and passes through the following points: (2014, 49.5), (2016, 62.3), (2018, 32.19), and ends at (2023, 53.3). The “Singapore” line starts at (2012, 6.25) and passes through the following points: (2014, 8.17), (2016, 5.28), (2018, 2.72), and ends at (2023, 1.4). The “Thailand” line starts at (2012, 49.48) and passes through the following points: (2014, 98.9), (2016, 49.48), (2018, 32.19), and ends at (2023, 38.27). The “Malaysia” line starts at (2012, 30) and passes through the following points: (2014, 32), (2016, 35.07), (2018, 35.3), and ends at (2023, 27.38). The “Indonesia” line starts at (2012, 62.3) and passes through the following points: (2014, 41.1), (2016, 55.2), (2018, 44.04), and ends at (2023, 65.18). The “Philippines” line starts at (2012, 39.2) and passes through the following points: (2014, 61), (2016, 76.7), (2018, 69.6), and ends at (2023, 46.6). At the bottom of the graph, the source reads: “Source(s): Compiled from The World Bank (2023 b)”. Note: All numerical data values are approximated.Appendix 3
Competencies of logistics managers in the new era
| Code | Indicative references | |
|---|---|---|
| Foundational competencies | ||
| FC1 | Adaptability | |
| FC2 | Leadership and emotional intelligence | |
| FC3 | Creative thinking and innovation | |
| FC4 | Collaboration and synergy | |
| FC5 | Communications | |
| FC6 | Customer centricity | |
| FC7 | Environmental sustainability mindset | |
| FC8 | Outcome-driven | |
| FC9 | Systems thinking | |
| FC10 | Ethical behaviour | |
| FC11 | Digital mindset | |
| FC12 | Resilient mindset | |
| FC13 | Judgement and decision making | |
| FC14 | Teamwork mindset | |
| FC15 | Growth mindset | |
| Core competencies | ||
| CC1 | Supply chain orientation | |
| CC2 | Supply chain strategy | |
| CC3 | Supply chain design | |
| CC4 | Supply chain and logistics analytics | |
| CC5 | Supply chain dynamics | |
| CC6 | Supply chain resilience | |
| CC7 | Logistics-transport regulations | |
| CC8 | Reverse supply chain | |
| Specialist competencies | ||
| SC1 | Transportation and distribution | |
| SC2 | Warehousing and facilities management | |
| SC3 | Forecasting and inventory management | |
| SC4 | Operations planning and execution | |
| SC5 | Procurement strategy and management | |
| SC6 | Order management and customer service | |
| SC7 | Packaging management | |
| SC8 | Returns management | |
| Technology-IT competencies | ||
| TC1 | Digital awareness and orientation | |
| TC2 | Data analytics/data processing | |
| TC3 | Optimisation and simulation ability | |
| TC4 | Computational competency | |
| TC5 | Understanding AI and machine learning applications | |
| TC6 | Understanding autonomous robotics applications | |
| TC7 | Understanding Internet of Things applications |
Source(s): Authors, adapted from the literature
Perceived importance of logistics managers’ competence
| Mean | Standard deviation | |
|---|---|---|
| Foundation competencies | ||
| FC1-Adaptability | 4.64 | 0.52 |
| FC13-Judgement and decision making | 4.60 | 0.53 |
| FC12-Resilient mindset | 4.57 | 0.55 |
| FC10-Ethical behaviour | 4.55 | 0.56 |
| FC14-Teamwork mindset | 4.54 | 0.59 |
| FC11-Digital mindset | 4.52 | 0.6 |
| FC8-Outcome-driven | 4.51 | 0.52 |
| FC9-Systems thinking | 4.51 | 0.56 |
| FC6-Customer centricity | 4.45 | 0.56 |
| FC5-Communications | 4.44 | 0.56 |
| FC15-Growth mindset | 4.41 | 0.53 |
| FC7-Environmental sustainability mindset | 4.41 | 0.6 |
| FC2-Leadership and emotional intelligent | 4.39 | 0.57 |
| FC3-Creative thinking and innovation | 4.38 | 0.56 |
| FC4-Collaboration and synergy | 4.33 | 0.54 |
| Core competencies | ||
| CC5-Supply chain dynamics | 4.28 | 0.60 |
| CC3-Supply chain design | 4.23 | 0.61 |
| CC6-Supply chain resilience | 4.23 | 0.64 |
| CC7-Logistics-transport regulations | 4.05 | 0.65 |
| CC4-Supply chain and logistics analytics | 3.99 | 0.66 |
| CC1-Supply chain orientation | 3.88 | 0.83 |
| CC2-Supply chain strategy | 3.86 | 0.79 |
| CC8-Reverse supply chain | 3.84 | 0.64 |
| Specialist competencies | ||
| SC6-Order management and customer service | 4.15 | 0.44 |
| SC7-Packaging management | 4.05 | 0.62 |
| SC5-Procurement strategy and management | 3.98 | 0.59 |
| SC4-Operations planning and execution | 3.96 | 0.65 |
| SC3-Forecasting and inventory management | 3.95 | 0.63 |
| SC1-Transportation and distribution | 3.92 | 0.62 |
| SC2-Warehousing and facilities management | 3.91 | 0.58 |
| SC8-Returns management | 3.90 | 0.66 |
| Technology-IT competencies | ||
| TC2-Data analytics/data processing | 4.25 | 0.47 |
| TC4-Computational competency | 4.23 | 0.54 |
| TC3-Optimisation and simulation ability | 4.05 | 0.67 |
| TC1-Digital awareness and orientation | 4.02 | 0.71 |
| TC6-Understanding autonomous robotics applications | 4.00 | 0.74 |
| TC5-Understanding AI and machine learning applications | 3.97 | 0.78 |
| TC7-Understanding Internet of Things applications | 3.94 | 0.80 |
| Mean | Standard deviation | |
|---|---|---|
| Foundation competencies | ||
| FC1-Adaptability | 4.64 | 0.52 |
| FC13-Judgement and decision making | 4.60 | 0.53 |
| FC12-Resilient mindset | 4.57 | 0.55 |
| FC10-Ethical behaviour | 4.55 | 0.56 |
| FC14-Teamwork mindset | 4.54 | 0.59 |
| FC11-Digital mindset | 4.52 | 0.6 |
| FC8-Outcome-driven | 4.51 | 0.52 |
| FC9-Systems thinking | 4.51 | 0.56 |
| FC6-Customer centricity | 4.45 | 0.56 |
| FC5-Communications | 4.44 | 0.56 |
| FC15-Growth mindset | 4.41 | 0.53 |
| FC7-Environmental sustainability mindset | 4.41 | 0.6 |
| FC2-Leadership and emotional intelligent | 4.39 | 0.57 |
| FC3-Creative thinking and innovation | 4.38 | 0.56 |
| FC4-Collaboration and synergy | 4.33 | 0.54 |
| Core competencies | ||
| CC5-Supply chain dynamics | 4.28 | 0.60 |
| CC3-Supply chain design | 4.23 | 0.61 |
| CC6-Supply chain resilience | 4.23 | 0.64 |
| CC7-Logistics-transport regulations | 4.05 | 0.65 |
| CC4-Supply chain and logistics analytics | 3.99 | 0.66 |
| CC1-Supply chain orientation | 3.88 | 0.83 |
| CC2-Supply chain strategy | 3.86 | 0.79 |
| CC8-Reverse supply chain | 3.84 | 0.64 |
| Specialist competencies | ||
| SC6-Order management and customer service | 4.15 | 0.44 |
| SC7-Packaging management | 4.05 | 0.62 |
| SC5-Procurement strategy and management | 3.98 | 0.59 |
| SC4-Operations planning and execution | 3.96 | 0.65 |
| SC3-Forecasting and inventory management | 3.95 | 0.63 |
| SC1-Transportation and distribution | 3.92 | 0.62 |
| SC2-Warehousing and facilities management | 3.91 | 0.58 |
| SC8-Returns management | 3.90 | 0.66 |
| Technology-IT competencies | ||
| TC2-Data analytics/data processing | 4.25 | 0.47 |
| TC4-Computational competency | 4.23 | 0.54 |
| TC3-Optimisation and simulation ability | 4.05 | 0.67 |
| TC1-Digital awareness and orientation | 4.02 | 0.71 |
| TC6-Understanding autonomous robotics applications | 4.00 | 0.74 |
| TC5-Understanding AI and machine learning applications | 3.97 | 0.78 |
| TC7-Understanding Internet of Things applications | 3.94 | 0.80 |
Note(s): 1 = Not at all important, 5 = Extremely important
Source(s): Authors’ own work
Appendix 4
Firms’ and respondents’ demographic information
| n | % | |
|---|---|---|
| Position | ||
| Senior Manager | 116 | 43.12 |
| Sale Manager | 69 | 25.65 |
| Account Manager | 84 | 31.23 |
| Working experience | ||
| ≤1 year | 2 | 0.74 |
| 2–5 years | 81 | 30.11 |
| 6–10 years | 107 | 39.78 |
| 11–20 years | 78 | 29.00 |
| ≥20 years | 1 | 0.37 |
| Educational qualification | ||
| Vocational college diploma | 1 | 0.37 |
| Bachelor degree | 187 | 69.52 |
| Master degree | 80 | 29.74 |
| PhD degree | 1 | 0.37 |
| Type of firm | ||
| Limited liability | 150 | 55.76 |
| State-owned | 3 | 1.12 |
| Stock-holding | 109 | 40.52 |
| Private | 3 | 1.12 |
| Joint-venture | 1 | 0.37 |
| Foreign-owned | 2 | 0.74 |
| Others | 1 | 0.37 |
| Employees number | ||
| 11–50 | 77 | 28.62 |
| ≤51–100 | 125 | 46.47 |
| ≥100 | 67 | 24.91 |
| n | % | |
|---|---|---|
| Position | ||
| Senior Manager | 116 | 43.12 |
| Sale Manager | 69 | 25.65 |
| Account Manager | 84 | 31.23 |
| Working experience | ||
| ≤1 year | 2 | 0.74 |
| 2–5 years | 81 | 30.11 |
| 6–10 years | 107 | 39.78 |
| 11–20 years | 78 | 29.00 |
| ≥20 years | 1 | 0.37 |
| Educational qualification | ||
| Vocational college diploma | 1 | 0.37 |
| Bachelor degree | 187 | 69.52 |
| Master degree | 80 | 29.74 |
| PhD degree | 1 | 0.37 |
| Type of firm | ||
| Limited liability | 150 | 55.76 |
| State-owned | 3 | 1.12 |
| Stock-holding | 109 | 40.52 |
| Private | 3 | 1.12 |
| Joint-venture | 1 | 0.37 |
| Foreign-owned | 2 | 0.74 |
| Others | 1 | 0.37 |
| Employees number | ||
| 11–50 | 77 | 28.62 |
| ≤51–100 | 125 | 46.47 |
| ≥100 | 67 | 24.91 |
Source(s): Authors’ own work
Current level of possession of logistics managers’ competence
| Mean | Standard deviation | |
|---|---|---|
| Foundation competencies | ||
| FC15-Growth mindset | 4.48 | 0.56 |
| FC9-Systems thinking | 4.43 | 0.58 |
| FC2-Leadership and emotional intelligence | 4.43 | 0.56 |
| FC11-Digital mindset | 4.42 | 0.58 |
| FC8-Outcome-driven | 4.32 | 0.59 |
| FC1-Adaptability | 4.30 | 0.63 |
| FC10-Ethical behaviour | 4.30 | 0.74 |
| FC4-Collaboration and synergy | 4.30 | 0.62 |
| FC3-Creative thinking and innovation | 4.25 | 0.73 |
| FC13-Judgement and decision making | 4.25 | 0.83 |
| FC7-Environmental sustainability mindset | 4.20 | 0.82 |
| FC5-Communications | 4.17 | 0.78 |
| FC12-Resilient mindset | 4.16 | 0.8 |
| FC14-Teamwork mindset | 4.14 | 0.8 |
| FC6-Customer centricity | 4.14 | 0.83 |
| Core competencies | ||
| CC5-Supply chain dynamics | 4.12 | 0.5 |
| CC6-Supply chain resilience | 4.10 | 0.6 |
| CC3-Supply chain design | 4.08 | 0.58 |
| CC4-Supply chain and logistics analytics | 3.92 | 0.63 |
| CC7-Logistics-transport regulations | 3.91 | 0.7 |
| CC8-Reverse supply chain | 3.84 | 0.61 |
| CC1-Supply chain orientation | 3.74 | 0.69 |
| CC2-Supply chain strategy | 3.71 | 0.68 |
| Specialist competencies | ||
| SC7-Packaging management | 4.00 | 0.65 |
| SC5-Procurement strategy and management | 3.94 | 0.61 |
| SC8-Returns management | 3.90 | 0.65 |
| SC4-Operations planning and execution | 3.89 | 0.66 |
| SC3-Forecasting and inventory management | 3.89 | 0.64 |
| SC1-Transportation and distribution | 3.87 | 0.68 |
| SC2-Warehousing and facilities management | 3.84 | 0.62 |
| SC6-Order management and customer service | 3.84 | 0.65 |
| Technology-IT competencies | ||
| TC4-Computational competency | 4.21 | 0.54 |
| TC2-Data analytics/data processing | 4.21 | 0.53 |
| TC3-Optimisation and simulation ability | 4.02 | 0.73 |
| TC1-Digital awareness and orientation | 3.99 | 0.74 |
| TC6-Understanding autonomous robotics applications | 3.94 | 0.82 |
| TC5-Understanding AI and machine learning applications | 3.93 | 0.79 |
| TC7-Understanding Internet of Things applications | 3.92 | 0.81 |
| Mean | Standard deviation | |
|---|---|---|
| Foundation competencies | ||
| FC15-Growth mindset | 4.48 | 0.56 |
| FC9-Systems thinking | 4.43 | 0.58 |
| FC2-Leadership and emotional intelligence | 4.43 | 0.56 |
| FC11-Digital mindset | 4.42 | 0.58 |
| FC8-Outcome-driven | 4.32 | 0.59 |
| FC1-Adaptability | 4.30 | 0.63 |
| FC10-Ethical behaviour | 4.30 | 0.74 |
| FC4-Collaboration and synergy | 4.30 | 0.62 |
| FC3-Creative thinking and innovation | 4.25 | 0.73 |
| FC13-Judgement and decision making | 4.25 | 0.83 |
| FC7-Environmental sustainability mindset | 4.20 | 0.82 |
| FC5-Communications | 4.17 | 0.78 |
| FC12-Resilient mindset | 4.16 | 0.8 |
| FC14-Teamwork mindset | 4.14 | 0.8 |
| FC6-Customer centricity | 4.14 | 0.83 |
| Core competencies | ||
| CC5-Supply chain dynamics | 4.12 | 0.5 |
| CC6-Supply chain resilience | 4.10 | 0.6 |
| CC3-Supply chain design | 4.08 | 0.58 |
| CC4-Supply chain and logistics analytics | 3.92 | 0.63 |
| CC7-Logistics-transport regulations | 3.91 | 0.7 |
| CC8-Reverse supply chain | 3.84 | 0.61 |
| CC1-Supply chain orientation | 3.74 | 0.69 |
| CC2-Supply chain strategy | 3.71 | 0.68 |
| Specialist competencies | ||
| SC7-Packaging management | 4.00 | 0.65 |
| SC5-Procurement strategy and management | 3.94 | 0.61 |
| SC8-Returns management | 3.90 | 0.65 |
| SC4-Operations planning and execution | 3.89 | 0.66 |
| SC3-Forecasting and inventory management | 3.89 | 0.64 |
| SC1-Transportation and distribution | 3.87 | 0.68 |
| SC2-Warehousing and facilities management | 3.84 | 0.62 |
| SC6-Order management and customer service | 3.84 | 0.65 |
| Technology-IT competencies | ||
| TC4-Computational competency | 4.21 | 0.54 |
| TC2-Data analytics/data processing | 4.21 | 0.53 |
| TC3-Optimisation and simulation ability | 4.02 | 0.73 |
| TC1-Digital awareness and orientation | 3.99 | 0.74 |
| TC6-Understanding autonomous robotics applications | 3.94 | 0.82 |
| TC5-Understanding AI and machine learning applications | 3.93 | 0.79 |
| TC7-Understanding Internet of Things applications | 3.92 | 0.81 |
Note(s): 1 = Very low, 5 = Very high
Source(s): Authors’ own work
