Key knowledge domains for maritime shipping executives in the digital era: a knowledge-based view approach

ABSTRACT

With the emergence of disruptive technologies and digital acceleration caused by COVID-19, educating the maritime workforce by equipping them with relevant knowledge is crucial to the industry’s success. Drawing from the knowledge-based view and business logistic management framework, the objective of this study was to construct a framework that identifies and ranks existing and upcoming relevant knowledge domains and their sub-domains for maritime shipping executives. After reviewing the literature, five domains – digitalisation, maritime business, sustainability, personnel development, and supply chain management (SCM) – and 23 sub-knowledge domains were developed. Surveys were conducted with shipping company managers in Singapore and their responses were analysed using the fuzzy analytic hierarchy process methodology. The results revealed that digitalisation knowledge was the most important, followed by maritime business, personnel development, sustainability, and SCM knowledge. Overall, this research has updated the knowledge and competency framework for maritime shipping executives, contributed to research on the interface between technology and knowledge management, and informed education strategies.

KEYWORDS:

• Industry 4.0
• knowledge-based view
• BLM framework
• maritime education
• competency framework

1. Introduction

The Fourth Industrial Revolution (hereafter Industry 4.0) transcends physical, biological, and digital boundaries through the unification of complex technologies. Emerging technologies include augmented reality (that digitises production processes), cloud computing (that handles information storage), big data (that converts information into useful knowledge), digital security (that protects data), and the Internet of Things (IoT) that ubiquitously connects all objects (Ardito, D'Adda, and Messeni Petruzzelli 2018; Ardito et al. 2019). Collectively, they can radically transform the market (Mandolla et al. 2019), introduce new macro-level competitive dynamics, and necessitate significant adjustments in company-level operations and competencies to exploit available opportunities (Appio et al. 2021; Ceipek et al. 2021). Thus, digital transformation induces firms to redesign knowledge management strategies (D’Ippolito, Messeni Petruzzelli, and Panniello 2019), open up new professional roles in management, and upskill executives to use emerging technologies to their fullest potential (Correani et al. 2020).

The effects of digital transformation can be felt by the maritime industry in the changes to traditional maritime business models and the provision of new revenue and opportunities (Sanchez-Gonzalez et al. 2019). However, emerging technologies cannot take the place of creativity, instinct, serendipity, and intellectual assets (Usai et al. 2021). Thus, executives cannot fully rely on technologies and forego their own upskilling. The criticality of knowledge domains shows that maritime educational requirements have a strong connection with Industry 4.0. To plan their curriculum, maritime education institutions collaborate with various maritime disciplines such as technology providers, shipping, and insurance sectors to gather knowledge about the required maritime business skills; however, there are currently no systematic approaches to integrating these sectors (Oksavik et al. 2020). Consequently, the maritime curriculum has failed to keep pace with the digital era, which will likely result in a future maritime workforce that lacks relevant competence (Buitendijk 2020). Hence, maritime curricula need to introduce upcoming knowledge domains.

The knowledge-based view (KBV) emphasises the importance of organisational knowledge for competitiveness and success (Pereira and Bamel 2021). However, the KBV is a broad concept and does not identify which knowledge is required in a specific field. Much literature on maritime executives has applied the business logistic management (BLM) framework to highlight required competencies (Daud, Adnan, and Mahmud 2019; Gordon and Cheah 2019; Kotzab et al. 2018). However, the BLM framework does not capture upcoming knowledge domains that are increasing in importance in the digital era. Furthermore, limited literature has investigated knowledge management from an interdisciplinary point of view, where different perspectives are considered collectively (Fruth and Teuteberg 2017; Keane et al. 2017). This is important because disruptions such as COVID-19 impact everyone, and businesses do not want to be under-prepared due to insufficient knowledge.

The objectives of this study are to (1) identify and collectively analyse existing and upcoming knowledge domains needed by maritime shipping executives in the digital era, and then (2) rank them in terms of their importance for the maritime curriculum. The main perspectives are:

1. Digitalisation: maritime businesses are adopting technological innovations such as automation, data analytics, and robotics (Chen et al. 2018b)

2. Maritime business: includes different functions such as administrative, operational, and managerial support (Kitada and Bhirugnath-Bhookhun 2019)

3. Sustainability management: enables businesses to enjoy more opportunities and competitive advantages (Chen, Wu, and Tsai 2018a)

4. Personnel development: soft skills have been identified as key employability skills in this decade (Chen et al. 2018b)

5. Supply chain management (SCM): overcomes organisational challenges, thereby enhancing efficiency, customer satisfaction, and market share (Akkucuk 2016)

Overall, this study gave equal attention to the identified knowledge domains, leading to an updated and holistic competency framework for maritime shipping executives. This framework will aid maritime education institutions to identify hot topics and modify their curricula accordingly, so that upcoming maritime graduates are better prepared for the digital era.

2. Literature review

2.1. Theoretical background: KBV and BLM

According to the KBV, knowledge is a critical asset that enhances companies’ competitiveness to achieve success (Pereira and Bamel 2021). Knowledge-based sources, which are embedded within the company, are socially complex, difficult to imitate, and constantly evolving (Chowdhury et al. 2022). Consequently, companies that have outstanding knowledge management capabilities can achieve a sustainable competitive advantage and respond quickly to dynamic business environments. Presented with such possibilities, companies are motivated by the KBV to enhance organisational knowledge, for example by upskilling individual’s skillsets (Flöthmann, Hoberg, and Gammelgaard 2018). However, the KBV does not define how to distribute knowledge in a way that fosters and fulfills individual outcomes (Chowdhury et al. 2022). Because the KBV does not specify which knowledge is crucial, it must be contextualised in terms of the specific industry and competitive environment.

To overcome this limitation, this study examined the BLM framework developed by Poist (1984), which is a competency framework that lists the business, logistics, and management competencies required by entry-level and senior-level logisticians. It has been applied extensively in various countries including Singapore, Malaysia, Australia, and Egypt (Thepmongkorn and Pitchayadejanant 2020), indicating that it is well-established and validated. However, there have been macroenvironment changes such as globalisation, climate change, and technological advancements since the introduction of the framework, and Li et al. (2021) point out that the framework has failed to account for digitalisation, geo-political, and sustainability-related competencies. Hence, there have been extensions of the BLM framework. Murphy and Poist (2007) added skills related to supplier and customer relations, creativity, and information and communication management. Gammelgaard and Larson (2001) included teamwork, supply chain awareness, and critical thinking.

From the maritime perspective, Li et al. (2021), Thai and Yeo (2012), and Thai, Yeo, and Pak (2016) have adapted the BLM framework for maritime executives. Specifically, Li et al. (2021) analysed BLM and digitalisation skills while Thai and Yeo (2012) acknowledged the importance of BLM skills but also emphasised the inclusion of specific maritime-related competencies. Consequently, this study will retain the BLM knowledge domains for our competency framework and include industry-specific domains that are crucial for maritime shipping executives.

A critical review of literature was conducted, and the identified knowledge domains are presented in Table 1 and Figure 1. The importance of BLM competencies in the form of maritime business, supply chain management, and personnel development were agreed in the literature. In addition, there was strong consensus on digitalisation and sustainability-related knowledge domains. Thus, this study updated the BLM framework to include digitalisation and sustainability-related perspectives.

Figure 1. Knowledge domains.

Table 1. Compiled knowledge domains.

	Digitalisation					Maritime Business				Sustainability Management
	Autonomous Technology	Artificial Intelligence (AI) and Big Data	Virtual, Augmented, and Mixed realities	Digital Security	IoT and Cloud Computing	Commercial	Legal	Technical	Financial	Resource Management	Labour Safety	Sustainable Business Practices	Community and Employee Management	Sustainability-related Laws and Regulations
(Cicek, Akyuz, and Celik 2019)		x					x	x		x	x	x	x
(Li et al. 2021)		x		x	x	x		x				x	x	x
(Thymara 2020)				x			x	x			x	x		x
(Oksavik et al. 2020)	x	x	x		x		x	x	x	x		x
(Pan et al. 2019)		x				x						x	x	x
(Li, Duan, and Liu 2019)	x	x	x	x			x	x
(Thai and Yeo 2012)		x				x	x		x		x	x	x
(Orfanou, Vlahogianni, and Yannis 2020)		x	x		x		x	x			x	x
(Thai, Yeo, and Pak 2016)		x				x	x		x		x		x
(Gammelgaard et al. 2013)	x				x	x		x		x				x
	Personnel Development					SCM
	Social	Personal	Organisational	Cooperative	Creative Thinking	Supply Chain Resilience	Customer Service	Supply Chain Strategy	Partner and Supplier Management
(Li et al. 2021)	x		x				x	x	x
(Thymara 2020)		x		x	x	x	x		x
(Oksavik et al. 2020)		x	x						x
(Pan et al. 2019)	x	x	x		x	x		x
(Thepmongkorn and Pitchayadejanant 2020)	x		x		x	x	x	x	x
(Thai and Yeo 2012)	x	x	x		x		x	x	x
(Thai, Yeo, and Pak 2016)			x	x	x	x	x		x
(Ding, Kuo, and Tai 2019)	x	x		x		x		x
(Gammelgaard et al. 2013)				x			x		x
(SoftSkills4EU 2019)	x	x	x	x	x		x	x

2.2. Competency profile for maritime shipping executives

2.2.1. Digitalisation knowledge

Autonomous technology consists of technological instruments such as automated guided vehicles, automated pallet-handling systems, and autonomous ships that enable autopilot controls in ports, warehouses, and shipyards. Thus, executives must enhance their knowledge about ICT systems’ programming languages, systems engineering skills, and situation awareness. This can be achieved by acquiring knowledge about automation collaboration and human-autonomy teaming (Westin et al. 2019).

Artificial intelligence (AI) and big data: the term big data denotes a vast quantity of data available, while AI involves machines making decisions based on those data (Munim et al. 2020). They drive data-driven decision-making processes in maritime domains through digitalisation and environmental performance (Yuen, Xu, and Lam 2020). Thus, executives can use predictive analytics, big data, and AI applications to optimise vessels’ performance, plan maritime routes, and enhance sustainability practices (Munim et al. 2020).

Virtual, augmented, and mixed realities are interactive interfaces with realistic simulations that optimise business decisions and enable training to take place outside the operating environment (Lvov and Popova 2019). These immersive environments cultivate professional thinking and promote the acquisition of physical and soft skills and capabilities (Lvov and Popova 2019). For example, simulator-based training can expand personal management skills and promote transversal competence (Oksavik et al. 2020). Furthermore, they expose users to different operational situations such as crane operations (Mallam, Nazir, and Renganayagalu 2019), and emergency preparedness training about crisis management such as fire and oil spills (Mallam, Nazir, and Renganayagalu 2019).

Digital security pertains to the enhancement of security interfaces to combat the increasing threat of digital attacks (Gamboa, Ramírez-Cabrales, and Jiménez 2020; Sanchez-Gonzalez et al. 2019). Maersk (the port of Antwerp) and oil drilling platforms have experienced cyber-attacks (Gamboa, Ramírez-Cabrales, and Jiménez 2020) that have attempted to hack business databases to gain access to billing information, cargo tracking systems (Bolat, Yüksel, and Uygur 2016), and disrupt port operations by interrupting GPS signals and overrunning automated port equipment (Bolat, Yüksel, and Uygur 2016). Moreover, the ease by which data can be collected has initiated security and privacy issues such as access control, secure data storage, and data integrity (Čolaković and Hadžialić 2018).

IoT and cloud computing: IoT integrates the internet’s physical components, thus connecting humans and devices (Zehir and Zehir 2020). Meanwhile, cloud computing enables users to access databases on the internet (Mraković and Vojinović 2019). With IoT and cloud computing, users can track and monitor the condition and location of cargo in real-time through cellular networks and sensors (Rainmaking 2018). In addition, these data-sharing platforms provide users with ocean and climate data, hence improving transparency, traceability, and resource planning, which ultimately leads to more efficient and safer shipments (Rainmaking 2018).

2.2.2. Maritime business knowledge

Commercial knowledge: shipping companies implement effective marketing strategies to increase revenue. To provide exemplary cargo management services, executives engage the most suitable types of ship for liner and tramp cargoes and design stowage plans for optimum cargo compatibility and stability (ICS 2016b). In addition, they provide shipbroking and chartering services. Hence, they must assess documentation and identify fraud because they handle different contracts relating to charter parties, sales, as well as the purchase and building of new ships.

Legal knowledge: Shipping is subject to international maritime conventions, laws, and insurances. These conventions include safety, security, environment, and seafarer qualification, as well as labour aspects of shipping (Mismarine 2020). Executives must understand business obligations under these conventions and ensure that business operations meet the required standards. Maritime law covers bills of lading and charter party contracts, conflict of laws, and dispute resolution instruments (Lloyds Maritime Academy 2020b), and executives need to be aware of responsibilities under maritime law to avoid legal difficulties. Maritime insurance covers hull, machinery, and cargo liability (ICS 2018), which requires executives to apply insurance risk and cover when necessary to reduce legal pressures faced by businesses.

Technical knowledge ensures vessels operate efficiently, safely, and reliably through crewing, maintenance, and technical consultancy. To ensure there are sufficient qualified crew to look after vessels, executives must understand crew standards and recruitment processes (ICS 2016b). Moreover, maintenance works on vessel systems (i.e. switchboards and diesel generators) must be performed ensure vessels remain seaworthy (OCIMF 2019).

Financial knowledge: Shipping is cyclical in character. Executives must be knowledgeable about financial instruments to enhance business during peak times and to ensure survival during troughs. This relates to economics and its concepts (such as opportunity costs and pricing behaviors) to maximise profits (ICS 2016a). Accounting and financial reports enabling decision making on budgets, appraisal of investments, and management of capital by analysing revenue, capital, and operating costs of current ships, costs of buying new ships, and revenue from selling them (Lloyds Maritime Academy 2020a).

2.2.3. Sustainability management knowledge

Resource management refers to efforts to protect the environment. These are major considerations that can affect business reputation and branding (Chen, Wu, and Tsai 2018a). Alternate energy sources, market-based instruments, and technical and operational measures can be applied to reduce greenhouse gas emissions (Koustoumpardis 2019); hence, executives must make informed decisions that can enhance their company’s environmental performance.

Labour safety systems relate to how businesses mitigate occupational risks faced by employees (Chen, Wu, and Tsai 2018a). Between 75% and 96% of maritime casualties are attributed to human factors. Hence, executives must implement and enforce maritime safety standards (such as the International Safety Management [ISM] Code) and the Maritime Labour Convention (2006) to better safeguard employees’ health (Shan and Lippel 2019).

Sustainable business practices satisfy customers’ and shareholders’ expectations by pushing businesses to be ethical, transparent, and socially responsible while performing well in terms of costs, investments, and audits (Chen, Wu, and Tsai 2018a). To enhance sustainable shipping practices, executives must apply high standards regarding business sustainability disclosures and ensure that relevant and accurate information about the businesses’ financial and operational performance is released (Lu, Lin, and Tu 2009).

Community and employee management includes cultivating employees with morality, integrity, and teaching them about social sustainability (Chen, Wu, and Tsai 2018a). Community involvement might include holding charitable events, and contributing to community welfare developments and education programmes by endorsing scholarships and employing interns (Lu, Lin, and Tu 2009). Meanwhile, employees’ entitlement encompasses measures to ensure their work-life balance, ample opportunities to upgrade their skills, and equal, non-biased employment with regard to race, religion, and gender (Lu, Lin, and Tu 2009; Yuen, Thai, and Wong 2017).

Sustainability-related laws and regulations are non-maritime regulations that cover sustainable purchasing, environment protection laws, and sustainable development goals (Chen, Wu, and Tsai 2018a), including the specific Sustainable Development Goals (SDGs) set by the United Nations. Executives must practice duty of care and ensure that their business activities comply with domestic or regional sustainability-related laws and regulations.

2.2.4. Personnel development knowledge

Social skills are used for communication, interaction, and learning (SoftSkills4EU 2019; Succi and Canovi 2020). To communicate effectively, executives must be active listeners and have judgment-free conversations to build bonds and prevent conflicts (Bates and Morgan 2018). They must also have inter-cultural skills to enhance their social awareness about prejudices and stereotypes so that people from different cultures and backgrounds do not feel excluded or discriminated against (SoftSkills4EU 2019).

Personal skills relate to personal development, emotional intelligence, and stress management (SoftSkills4EU 2019). Personal development requires employee self-reflection so that executives can assess whether they are motivated, genuinely interested in their jobs, and have exposure to opportunities to upgrade their skillsets (Bates and Morgan 2018). Emotional intelligence refers to how executives process, integrate, and handle their emotions for personal growth (Kapur 2018). Increased emotional intelligence will enable executives to improve teamwork, leadership, and conflict management skills (Rathore, Chadha, and Rana 2017).

Organisational skills refer to leadership and time management skills (SoftSkills4EU 2019). Leadership functions can be enacted through many different styles: coercive, authoritative, pacesetting, democratic, and coaching (Kapur 2018). Executives must decide which leadership style is most suitable for their organisation’s structure and culture before delegating tasks and objectives to subordinates. Time management can improve the organisation of professional lives if executives are proactive and consistent in preparing work charts and to-do-lists, and prioritise which tasks should be completed first (Aeon and Aguinis 2017).

Cooperative skills include teamwork, collaboration, and flexibility (SoftSkills4EU 2019). Businesses cannot risk the effects of politics, sabotage, and ill-feeling within their company. Collaboration requires executives to support each other and make consensual decisions together such that the best strategic decisions can be made (Khawam, DiDona, and Hernández 2017). Hence, executives must have synergy and work together for the ultimate good of the business (Tem, Kuroda, and Tang 2020).

Creative thinking skills generate out-of-the-box, transdisciplinary solutions that provide businesses with a new take on solving problems (Coberly-Holt and Elufiede 2019). These skills encourage innovation, creativity, and continuous improvement, which can help businesses release one-of-a-kind services that competitors cannot imitate (SoftSkills4EU 2019). Hence, businesses reap economic benefits and sustainable competitive advantages.

2.2.5. SCM

Supply chain resilience is vital because globalisation and lean processes are increasing the complexity and interdependency of supply chain networks (Li et al. 2020). Consequently, they are becoming more vulnerable to disruptions such as natural disasters (for example, earthquakes) and man-made disruptions (for example, port strikes and terrorism) (Hosseini, Ivanov, and Dolgui 2019). These events are unpredictable and can have disastrous effects. Executives must be ever ready and have crisis management tactics to offer quick responses.

Customer service requires a comprehensive understanding of customers’ commodity trading and logistics needs to provide shipping services catered to their needs (Sunil Chopra 2016). Today, customers desire product improvements, service benefits, and price reductions (Min, Zacharia, and Smith 2019), and executives must ensure that these specifications are addressed in their strategies.

Supply chain strategy relates to how manufacturers plan and design supply chain activities to enhance overall efficiency. Hence, market trends, demand forecasts, and business insights must be studied (Delipinar and Kocaoglu 2016). These analyses assist in the development of procurement plans and deciding on the optimal level of push–pull strategies. Once completed, executives can then determine the best transportation modes and locations of facilities (i.e. warehouses and distribution centres) and assign employees to support the strategies (Sundarakani, Abdul Razzak, and Manikandan 2018).

Partner and supplier management is essential for ensuring company performance continues to be strong and reliable. This requires executives to select the most appropriate partners and suppliers for strategic alliances, partnerships, and mergers and acquisitions. In addition, executives should be able to monitor and control suppliers’ and partners’ performances in areas such as service quality and on-time delivery as they impact the company’s overall operational and financial performance (Jajja et al. 2016).

3. Methodology

The steps of fuzzy analytical hierarchical process (FAHP) analysis are illustrated in Figure 2.

Figure 2. The analytical process.

3.1. Step 1. AHP model construction

The three-level hierarchy model comprising goal, main factors, and sub-factors is depicted in Figure 1 in the previous section. The selection of main factor and sub-factor are subjective; hence, to increase the reliability and validity of the research model, all factors were proposed on the basis of existing literature and have been reviewed by academic and industry experts majoring in maritime shipping. A total of five main factors and 23 sub-factors were included in the research model.

3.2. Step 2. Survey administration and data collection

A questionnaire survey was conducted to collect experts’ judgments on the relative importance of the factor. Following AHP principles, the questionnaire comprised two sections. In the first section, experts were asked to perform pair-wise comparison by choosing a response where ‘9 = extremely important’ and ‘1/9 = extremely unimportant’. In the second section, respondents’ demographic information was provided.

3.3. Step 3. Fuzzy judgment conversion and synthesis

Membership function was used to represent the degree of truth of extended values. The value ranges from 0 to 1, where a larger number implies a higher degree of belonging in fuzzy logic (Zadeh 1996). In this study, the obtained crisp judgments are converted into fuzzy judgments by applying the triangular fuzzy number (TFN), one of the most popular fuzzy judgment representation methods. As shown in Figure 3, a TFN comprises three points: an upper possible value ($u),$ a lower possible value ($l$), with the lowest associated membership, and a most promising value $\left(m\right)$; the largest associated membership is assigned to denote the imprecision of human thinking (Liu, Eckert, and Earl 2020). Let $\tilde{C}$ be a TFN expressed by $\left(l,m,u\right)$, a triangular membership function as illustrated in the following: (1) $\mu \left(x\right)=\{\begin{array}{c}{\displaystyle \frac{x-l}{m-l}\mathrm{\forall l}\le x\le m}\\ {\displaystyle \frac{h-x}{h-m}\mathrm{\forall m}\le x\le h}\end{array}$(1)

Figure 3. Triangular fuzzy number.

The conversion scale applied in this study is shown in Table 2.

Table 2. Fuzzy conversion scale.

Linguistic term	Scale	Triangular fuzzy scale
Equally important	1	(1,1,1)
Moderately important	3	(1,3,5)
Strongly important	5	(3,5,7)
Very strongly important	7	(5,7,9)
Extremely strongly important	9	(7,9,9)
Moderately unimportant	1/3	(1/5,1/3,1)
Strongly unimportant	1/5	(1/7,1/5,1/3)
Very strongly unimportant	1/7	(1/9,1/7,1/5)
Extremely strongly unimportant	1/9	(1/9,1/9,1/7)

Source: Nurani et al. (2017)

The TFN algebraic operations applied in the following calculations are explained thus: Let $\widetilde{c_1}$ = ($l_1,m_{1,}{u}_1$) and $\widetilde{c_2}$ = ($l_2,m_{2,}{u}_2)$ represent two TFNs: (2) $\mathrm{Addition}:\widetilde{c_1}\oplus \widetilde{c_2}=(l_1+l_{2,}{m}_1+m_2,u_1+u_2)$(2)

(3) $\mathrm{Multiplication}:\widetilde{c_1}\otimes \widetilde{c_2}=\left(l_1\times l_{2,}{m}_1\times m_2,u_1\times u_2\right)$(3) (4) $\mathrm{Reciprocal}:{\widetilde{c_1}}^{-1}=\left({\displaystyle \frac{1}{u_1},{\displaystyle \frac{1}{m_1},{\displaystyle \frac{1}{l_1}}}}\right)$(4) (5) $\mathrm{Exponent}:{\widetilde{c_1}}^{\frac{1}{q}}=(l_1^{\frac{1}{q}},m_1^{\frac{1}{q}},u_1^{\frac{1}{q}})$(5)

Next, eighty experts’ fuzzy judgments were synthesised through the geometric mean method. Let $\widetilde{c_{\mathrm{ij}}}=\left(l_{\mathrm{ij}},m_{\mathrm{ij}},u_{\mathrm{ij}}\right)$ be the synthesised judgment of $c_i$ over $c_j$, $k$ be the $k$ experts, and ($l_{\mathrm{ij}}^t,m_{\mathrm{ij}}^t,u_{\mathrm{ij}}^t)$ be the fuzzy judgment of expert $t\left(t=1,2,\dots ,k\right)$, for which the calculation formula is as follows: (6) $\widetilde{c_{\mathrm{ij}}}=\left({\left(\prod _{t=1}^k{l}_{\mathrm{ij}}^t\right)}^{{\displaystyle \frac{1}{k}}},{\left(\prod _{t=1}^k{m}_{\mathrm{ij}}^t\right)}^{{\displaystyle \frac{1}{k}}},{\left(\prod _{t=1}^k{u}_{\mathrm{ij}}^t\right)}^{{\displaystyle \frac{1}{k}}}\right)$(6)

3.4. Step 4. Fuzzy comparison matrix construction

Let $\tilde{C}$ represent an $n\times n$ matrix, where $n$ represents the number of factors in this group; thus, the fuzzy comparison matrix can be constructed as follows: (7) $\tilde{C}=(\widetilde{c_{\mathrm{ij}}}{)}_{n\times n}=\left[\begin{array}{ccc}\widetilde{c_{11}}& \cdots & \widetilde{c_{1n}}\\ ⋮& \ddots & ⋮\\ \widetilde{c_{n1}}& \cdots & \widetilde{c_{\mathrm{nn}}}\end{array}\right]$(7) (8) $\widetilde{c_{\mathrm{ij}}}=\{\begin{array}{c}\left(l_{\mathrm{ij}}{m}_{\mathrm{ij},}{u}_{\mathrm{ij}}\right)\mathrm{\forall i}<j\\ \left(1,1,1\right)\mathrm{\forall i}=j\\ \left({\displaystyle \frac{1}{u_{\mathrm{ij}}},{\displaystyle \frac{1}{m_{\mathrm{ij}}},{\displaystyle \frac{1}{l_{\mathrm{ij}}}}}}\right);\mathrm{\forall }i>j\end{array}$(8)

3.5. Step 5. Consistency ratio calculation

Because human judgment inconsistency might exist, this could lead to misleading results. To avoid such contradictions, the consistency test was proposed. A matrix with a consistency ratio (CR) less than 0.1 could be considered consistent (Saaty 1990). The formula is illustrated where CI refers to consistency index, ${\lambda }_{\max }$ refers to the maximum value of the matrix, and RI refers to the random consistency index (Table 3).

(9) $\mathrm{CR}={\displaystyle \frac{\mathrm{CI}}{\mathrm{RI}}}$(9) (10) $\mathrm{CI}={\displaystyle \frac{{\lambda }_{\max }-n}{n-1}}$(10)

Table 3. Random index.

Size	1	2	3	4	5
RI	0	0	0.52	0.89	1.11

Source: Saaty (1990)

3.6. Step 6. Fuzzy weights calculation

The geometric mean method was applied to calculate the eigenvalues of the matrix. The formula is shown as follows: (11) $\widetilde{Z_i}=(\widetilde{c_{i1}}\otimes \widetilde{c_{i2}}\otimes \dots \otimes {\widetilde{c_{\mathrm{in}})}}^{\frac{1}{n}}\mathrm{\forall }i=1,2\dots n$(11) (12) $\widetilde{w_i}=Z_i\times {\left(\sum _{i=1}^n{Z}_i\right)}^{-1}$(12)

3.7. Step 7. Non-fuzzy weights calculation and normalisation

The centroid method with best non-fuzzy performance (BNP) value was applied to defuzzify the obtained fuzzy weights: (13) $\mathrm{BNP}\mathrm{value}={\displaystyle \frac{\left(u_i-l_i\right)+\left(m_i-l_i\right)}{3}+l_i\mathrm{\forall i}=1,2,\dots n}$(13)

Then, to better compare the results, the BNP values were normalised based on the following formula: (14) $\mathrm{NBN}{P}_i={\displaystyle \frac{\mathrm{BN}{P}_i}{{\sum }_{i=1}^n\mathrm{BN}{P}_i}\mathrm{\forall i}=1,2,\dots n}$(14)

3.8. Step 8. Ranking of main factor and sub-factor

The calculation process was applied to each group subsequently. The local ranking of main factors and the sub-factors of each main factor could then be identified. Then, by multiplying the weights of a sub-factor with its parent factor, global weights of all sub-factors could be obtained. The details are discussed in the next section.

4. Results and discussion

4.1. Profile of respondents

The sampling frame for the survey administration was constructed using the Singapore Directory. In total, 422 records were obtained from the ‘shipping companies’ category, and a full population sample was conducted. The questionnaires were distributed to staff and managers employed by maritime shipping companies, as industry experts’ work experience and accumulated knowledge could assist them in exercising professional evaluations. Finally, 80 valid questionnaires were collected. Their profiles are shown in Table 4.

Table 4. Profile of respondents.

Characteristics	Items	Number	Percentage
Sector	Liner shipping	24	30%
	Dry or liquid bulk shipping	56	70%
Firm's age (years)	0–10	8	10%
	11–20	54	67%
	Over 21	18	23%
Number of employees	Below 100	14	18%
	101–200	49	61%
	Over 201	17	21%
Seniority (years)	6–10	40	50%
	11–15	18	23%
	Over 16	22	27%
Job position	Director and above	37	46%
	Manager	43	54%

It can be observed that among the respondents, 46.25% were directors and 53.75% were managers. Furthermore, 50% had 6–10 years’ work experience, 22.5% had 11–15 years, and 27.5% had over 16 years. Therefore, they could be considered experienced and qualified executives who can accurately rank the knowledge domains.

4.2. FAHP results

The consistency rate of all main factors was within the standard acceptable value of 0.1. Hence, the data collected were consistent and considered suitable for calculating the respective local and global weights of the main and subfactors. To do so, the FAHP methodology was applied, for which the results are presented in Table 5.

Table 5. FAHP results.

Main criteria	Local weights	CR	Sub-criteria	Local weights	Global weights	Global ranking
Digitalisation knowledge	0.3626	0.0352	Autonomous technology	0.2082	0.0755	4
			AI and big data	0.3519	0.1276	1
			Virtual, augmented, and mixed realities	0.0902	0.0327	12
			Digital security	0.1373	0.0498	8
			IoT and cloud computing	0.2125	0.0770	3
Maritime business knowledge	0.2429	0.0537	Commercial knowledge	0.4799	0.1166	2
			Legal knowledge	0.1881	0.0457	9
			Technical knowledge	0.2676	0.0650	6
			Financial knowledge	0.0644	0.0156	19
Sustainability management knowledge	0.1525	0.0598	Resource management	0.2099	0.0320	13
			Labour safety systems	0.2097	0.0319	14
			Sustainable business practices	0.4024	0.0614	7
			Community and employee management	0.0751	0.0115	22
			Sustainability-related laws and regulations	0.1029	0.0157	18
Personnel development knowledge	0.1638	0.0648	Social skills	0.4063	0.0666	5
			Personal skills	0.0847	0.0139	20
			Organisational skills	0.1095	0.0179	17
			Cooperative skills	0.2639	0.0432	10
			Creative thinking skills	0.1355	0.0222	16
SCM knowledge	0.0782	0.0201	Supply chain resilience	0.4677	0.0366	11
			Customer service	0.2892	0.0226	15
			Supply chain strategy	0.1660	0.0130	21
			Partner and supplier management	0.0771	0.0060	23

Among the local weights, the most important main factor was digitalisation knowledge (0.3626), followed by maritime business knowledge (0.2429), personnel development knowledge (0.1638), sustainability management knowledge (0.1525), and finally SCM knowledge (0.0782). This could be because technology is evolving at an accelerating pace, and digital readiness will be the differentiating factor between successful and less successful companies. As such, it is paramount for maritime shipping executives to expand and upgrade their digitalisation skills.

Among the digitalisation subfactors, AI and big data were the most important (0.3519), followed by IoT and cloud computing (0.2125), autonomous technology (0.2082), digital security (0.1373), and then virtual, augmented, and mixed realities (0.0902). AI and big data include the use of predictive analytics and other data analytic techniques to interpret data and short-list the most appropriate decisions. Meanwhile, IoT and cloud computing have digitalised traditional networks such that executives can access online data-sharing platforms and retrieve real-time information about the locations and conditions of various cargoes. Autonomous technology is becoming more prevalent as automated equipment grows in prevalence in the supply chain. Digital security knowledge is needed to prevent digital attacks from hacking into business systems and potentially disrupting operations and/or leaking sensitive information. Lastly, virtual, augmented, and mixed realities enable simulation to prepare executives for various operational and emergency situations.

For maritime business subfactors, commercial knowledge (0.2676) was most crucial, followed by technical knowledge (0.2703), legal knowledge (0.1881), and financial knowledge (0.0644). Commercial knowledge encompasses marketing strategies, stowage plans, and chartering services that directly impact shipping companies’ day-to-day operations, which will bring substantial revenue and ensure healthy cash flow to meet internal stakeholders’ expectations and ensure sustained growth. In addition, executives must possess the technical knowledge to monitor maintenance, bunkering, and repair operations and oversee training programmes to ensure ships remain seaworthy. Next, legal knowledge comprises knowledge about maritime regulatory frameworks such as manpower, safety, and security. This knowledge is particularly useful for executives to understand their liabilities and obligations. Finally, financial knowledge is ranked last because accounting and leasing may be considered repetitive procedures as the steps and guidelines rarely change. Thus, executives may perceive these as standardised operations that require less focus and attention compared to the other subfactors.

For sustainability management knowledge, sustainable business practices (0.4024) were ranked as the most important, succeeded by resource management (0.2099), labour safety systems (0.2097), sustainability-related laws and regulations (0.1029), and community and employee management (0.0751). Sustainable business practices are important for establishing transparent operations. If done immorally, the integrity and reliability of the shipping companies’ services will be compromised and may disrupt business relationships. Meanwhile, resource management enables better management of fuel utilisation and anthropogenic marine pollutants, which is instrumental in meeting stringent environmental regulations. Labour safety systems incorporate strong safety standards, compliance, and cultures. This reduces occupational risks and hazards. Next, non-maritime related sustainability-related laws and regulations indicate the different legal structures that shipping companies must comply with. Finally, community and employee management involves promoting ethics-driven attitudes and sustainable and socially responsible practices concerning people, profits, and the planet.

With regard to personnel development knowledge, social skills (0.4063) were most important, followed by cooperative skills (0.2639), creative thinking skills (0.1355), organisational skills (0.1095), and personal skills (0.0847). Social skills are essential for communicating effectively and listening actively to peers. Social awareness facilitates workplace productivity and collaboration to move the company forward. Cooperative skills are important for preventing dysfunctional conflicts. They must also adapt well to situations and be flexible. Creative thinking skills encourage innovation that can differentiate companies from their competitors and instigate some business opportunities. Organisational skills are needed to lead, manage time, and lead by delegating workload strategically so that optimal decisions can be made regarding finances and time. Lastly, personal skills relate to how well an individual manages their stress levels and individual motivation drivers for better resilience and certainty in their work.

For SCM knowledge, supply chain resilience (0.4677) was regarded the most critical, then customer service (0.2892), supply chain strategy (0.1660), and partner and supplier management (0.0771). Supply chain resilience is growing in cruciality as supply chain networks become more interdependent. Excellent crisis management skills are needed to counter natural and man-made disruptions. Customer service requires an in-depth understanding of customers’ requirements to tailor services according to their needs. Good customer service will be complemented by positive customer feedback and stronger customer loyalty. Next, planning and designing are key to supply chain strategy to derive optimal push–pull boundaries for better strategic fit and to protect company interests. Finally, partner and supplier management leverage relationship marketing and networking. If partners and suppliers are well-managed, there is less need for micro-management, which allows more time for constructive work.

5. Conclusion

5.1. Theoretical and policy implications

This research has several theoretical implications. First, it developed and updated a competency framework for maritime shipping executives. The well-known concept – KBV – did not specify the knowledge domains required in a field. In addition, the BLM framework failed to include upcoming knowledge domains despite them becoming more important in the digital era. Hence, this research proposed a more comprehensive framework that extends the BLM framework by including both traditional and upcoming knowledge domains to avoid potential knowledge gaps. Consequently, executives can adapt to industry changes and become valuable assets to shipping companies.

Second, the research discussed different perspectives holistically and balanced attention was given to the five main knowledge domains. Most previous literature only focused on one or a few perspectives and failed to provide an objective comparison of the knowledge domains in the digital era. Based on local weights, the results here imply that digitalisation knowledge is the most important. Similarly, when considering global weights, three of the five digitalisation sub-factors – AI and big data, IoT and cloud computing, and autonomous technology – were among the top five. Hence, it could be implied that digitalisation is the most crucial knowledge domain.

For policy implications, the developed theoretical competency framework can be applied to facilitate planning and designing maritime curricula. First, this research contextualises and categorises the knowledge domains into main and sub-factors. These topics can be incorporated into the maritime course content to ensure that students acquire relevant knowledge. Second, the framework provides institutions with an overview of hot topics in the maritime industry. Consequently, institutions can propose related topics for post-graduate research. Third, institutions can use the survey results as a basis for scoring their programmes based on how effectively they address current and future competency concerns. By doing so, institutions can identify the strengths and weaknesses of their programmes based on the scores. Hence, institutions can improve their course curricula by modifying existing programmes with low scores and adding new programmes that address upcoming competency requirements. When this practice is applied across various institutions, sharing of best practices and benchmarking results can be practiced.

5.2. Limitations and recommendations

First, the respondents were from shipping companies operating in Singapore. However, Industry 4.0 has far-reaching global impact. Different countries may be at different stages of digitalisation. Thus, the research findings of the most important knowledge factors and sub-factors may not apply to other countries, such as less developed countries that cannot afford to invest in digital technologies. The framework developed in this research should be generalised internationally to cross-validate the importance of factors and sub-factors.

Second, the survey was administered to shipping company executives as they make up the main bulk of maritime executives. However, not all undergraduates who are in the maritime programmes end up in the shipping sector. Some may join other sectors (e.g. maritime lawyers). Hence, there may have been some subjective evaluation by shipping company executives. For a more balanced and objective viewpoint, maritime executives from different sectors should also have been invited. Accordingly, consensus regarding the most important factor and sub-factors can be agreed upon by maritime executives in the industry.

A final recommendation is to research new instructional methods rather than relying on traditional methods such as face-to-face lessons. This is important, as the impact of the COVID-19 pandemic has resulted in a push for new instructional methods, such as home-based learning. These instructional methods have not yet been studied extensively. Future research might explore these instructional methods and update the competency framework accordingly.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Le Yi Koh

Ms Koh, Le Yi is currently a Ph.D. student at the School of Civil and Environmental Engineering, Nanyang Technological University, Singapore. Her research interest is on the interface between knowledge and technology management.

Xue Li

Ms Li, Xue is currently a PhD student at the School of Civil and Environmental Engineering, Nanyang Technological University, Singapore. Her research interest is on maritime studies, logistics management and technology management.

Xueqin Wang

Dr. Wang Xueqin is currently an assistant professor at Chung-Ang University, Korea. She received her Bachelor of Science (Maritime Studies) degree and Doctor of Philosophy degree from NTU in Jun-2014 and Sep-2018 respectively. Her research interests are in consumers’ participatory behaviours in last-mile logistics from a value co-creation perspective. Her research works can be found in Journal of Service Theory and practice, Journal of Retailing and Consumer Services, and International Journal of Physical Distribution and Logistics Management.

Kum Fai Yuen

Dr Yuen is currently Assistant Professor and Programme Director of MSc (Maritime Studies) at School of Civil and Environmental Engineering, Nanyang Technological University, Singapore. He is also the recipient of the Inauguration Grant 2019, an award under the Singapore Teaching and Academic Research Talent Scheme. Currently, he is serving as Associate Editor at Frontiers in Marine Science (SCI), Maritime Policy & Management (SSCI) and Asian Journal of Shipping and Logistics (ESCI), and Editorial Advisory Board Member for International Journal of Quality and Service Sciences (ESCI), Transportation Research: Interdisciplinary Perspectives (Scopus) as well as Continuity & Resilience Review. His research interests include maritime logistics, marine policies and management, sustainability, corporate social responsibility, last-mile delivery, shared transport and economy, and technology innovation management.