Employee adaptability skills for Industry 4.0 success: a road map

ABSTRACT

Industry 4.0 revolutionizes the concept of automation and digitization within the organization leading to immense interest in academia and industry. The digitization of an organization in terms of horizontal, vertical, and end-to-end integration would change the roles an employee discharges in an organization. The main purpose of the paper is to successfully develop an employee adaptability road map for the successful implementation of Industry 4.0. This paper critically analyses the previous studies to develop a roadmap of employee adaptability skills for the successful implementation of Industry 4.0. This study uses deductive methodology using a systematic literature review to group and thematically analyse 52 articles to develop the conceptual model. Besides, this study also ranks these dimensions using an empirical study and finds the most critical employee adaptability dimensions. This is the first systematic literature review and empirical study carried out on employee adaptability skills in Industry 4.0.

KEYWORDS:

• Industry 4.0
• cyber-physical-systems
• knowledge society
• employee adaptability
• literature review

1. Introduction

Industry 4.0 represents the current trend in automation and computing technologies such as cyber-physical systems (CPS), Internet of things (IoT), and cloud computing, which an organization uses to transform its day-to-day activities (Antony et al., 2021; Liao et al., 2017; Sony, 2018). Industry 4.0 is predominantly based on nine technologies: ‘autonomous robots, system integration, the internet of things (IoT), simulation, additive manufacturing, cloud computing, augmented reality, big data, and cybersecurity’ (Kaur et al., 2020). These nine technologies will be used by organizations to manufacture smart products and services and employees will have to adapt to using the technologies. Another point to consider is that Industry 4.0 is not the only application of technology rather, but also joint optimization of social and technical systems working in an integrated manner to meet the objectives and goals of the organization (Sony & Naik, 2020b). Furthermore, it further warrants employees to adapt to multiple dimensions for the successful implementation of Industry 4.0. The employee’s ability to deal with such dynamic work situations will be an important facet in the success of Industry 4.0. Previous studies on employee adaptability have depicted that the individual employee capacity for adaptation varies in such dynamic work situations. Besides the capability to modify behaviour according to the requirements of new environments, situations or events is a prime requirement for employee adaptability (Charbonnier‐Voirin & Roussel, 2012; Ilgen & Pulakos, 1999; Pulakos et al., 2000; Sony & Mekoth, 2014). One more thing to consider is that lack of skills may slow down the benefits of Industry 4.0 technologies, which may affect the company’s performance. In a study by McKinsey most companies that have implemented digital transformation, have failed to capture the full business opportunities available from new technologies. Some of the challenges the organization face in the scaling of digital transformation are lack of a strategic direction as regards how digital manufacturing will bring real business value, lack of required technical, managerial & transformational capabilities, and lack of robust data and IT infrastructure(De Boer et al., 2020). The success rate of digital transformation initiatives in an organization is less than 30%. The five key factors for the successful digital transformation are (1) having the right digital-savvy leaders, (2) workforce building, (3) empower employees to work in a new manner, (4) day-to-day tools a digital upgrades and communication (Hortense et al., 2018). Analyzing these factors show that three factors are related to humans. It, therefore, depicts the importance of human elements especially employees in the success of the digital transformation. Employee adaptability is the meta-skill that will help the employees to handle the digital transformation such as Industry 4.0. The main purpose of the paper is to develop an employee adaptability road map for the successful implementation of Industry 4.0. Subsequently, the study investigates the most critical employee adaptability dimensions for the success of Industry 4.0 implementation. The remainder of the paper is organized as follows, the theoretical background is delineated next, followed by the methodology section, results, proposed conceptual model, discussion, limitation and future research, and conclusion.

2. Theoretical background

Employee performance was classified as an indicator that measured how successful or not successful an employee is at the workplace. Adaptative performance was an important construct that was used to measure adaptability at the workplace (Charbonnier‐Voirin & Roussel, 2012). Employee adaptability at the workplace was initially conceptualized by Pulakos et al. (2000). They conceptualized adaptability as an eight-dimensional construct. The dimensions were ‘(1) dealing with uncertain or unpredictable situations, (2) handling emergencies or crises, (3) solving problems creatively, (4) handling work stress, (5) learning new tasks, technologies, and procedures (6) demonstrating interpersonal adaptability, (7) demonstrating cultural adaptability, (8) demonstrating physically oriented adaptability’ (Pulakos et al., 2000). Further research on employee adaptability transpired that the dimensions of employee adaptability changes depending upon the type and nature of Job (Charbonnier‐Voirin & Roussel, 2012). Besides, employee adaptability was suggested as a construct that changes with the dynamic changes that are happening at work (Van Dam, 2013). Thus, adaptability studies were explored in various sectors and different contexts. To cite an instance, Sony and Mekoth (2014), Sony & Mekoth (2015) developed scales of employee adaptability in the power sector. There was also the development of scales of adaptability in the hospitality sector (Rasheed et al., 2020) and other sectors. Though adaptability is a well-researched concept, however, there is still a need for a validated scale that assesses employee adaptability as an individual difference construct (Van Dam & Meulders, 2020). Besides, these dimensions of employee adaptability were context-dependent and continuously changing with the modern work scenarios. With the implementation of Industry 4.0 smart working has changed the manner work is carried out in an organization. Besides, smart supply chains and smart manufacturing (Frank et al., 2019) have changed the manner the work is carried out in a modern workplace. Hence, there is a need to collate and analyse the existing research efforts to bring clarity to understand the elements of successful employee adaptability in the Industry 4.0 era.

3. Research methodology

The research methodology for this paper consists of deductive methodology, systematic literature review and grouping methodology.

3.1. Deductive methodology

The authors intend to develop a framework and hence intends to collate previous research to develop a framework and hence deductive methodology would be the theoretical underpinnings in the study (Al-Ababneh, 2020). The deductive method usually begins from a theoretical base (Woiceshyn & Daellenbach, 2018). The first point for generating a theoretical base is collecting research articles. If the starting point is not grounded in theory, the study will be criticized (Locke, 2007). Hence, a systematic research methodology was conceptualized as it helps to collect the articles which can be used to answer the proposed research aims and objectives (Denyer & Tranfield, 2009).

3.2. Systematic literature review

The first phase involves searching electronic databases. The search string about Industry 4.0 was adopted from the previous literature review on Industry 4.0 by Liao et al. (2017) and Sven-Vegard Buer et al. (2018). Based on the keywords, the search string was designed in two parts for this study. Appendix A depicts the search strategy used in this study. Part 1 and part 2 was used for extracting related literature for the study. The present study included conference articles to extract insights relating to emerging research areas (Flick, 2015). A protocol developed by Popay et al. (2006) was used to limit systematic error and bias in the screening of papers for review.

We include texts that:

• directly answer any one or more of our research questions;

• were published till October 2020;

• screening criteria, in the title or abstract of the article

We exclude texts

• in the form of overhead presentations or unpublished articles.

• opinion pieces, viewpoints or purely anecdotal.

• articles appeared in the journal from Beall’s list or Cabell’s list (Beall, 2012; Berger & Cirasella, 2015; Das & Chatterjee, 2018)

Our preliminary search revealed 315 pieces of literature. After reading the title, abstract and duplication only 68 articles remained. Further analysis was carried out by a detailed reading of the articles. All the articles from unpublished sources were removed and the final sample of 52 articles was selected. We used free software Mendeley to record the reference details related to each article.

3.3. Grouping methodology

The papers were read by the authors. The first phase consisted of first-order thematic classification (Gruenhagen et al., 2020) of employee skills and ability requirements for Industry 4.0. The skills and ability were classified as an individual standalone meaning unit. In Phase 2, the second-order thematic classification of the skills and abilities were carried out for merging the first-order themes to create a higher-order categorisation of skills and abilities. This was done by collating the similar theme of skills into a higher-order theme (S. Chen et al., 2020). The themes were also calculated to represent the frequencies of the number of times each theme is identified in different studies.

4. Results

To explore the dimensions of employee adaptability in Industry 4.0 environment, the previous literature was thematically analysed to group them in a meaningful cluster of higher-order themes (Cronin et al., 2008). This helped us to categorise the employee adaptability dimensions in Industry 4.0

4.1. Interpersonal adaptability in Industry 4.0

The employees need to adjust their work as per the interpersonal needs of employees from their organization or other organization. The interpersonal needs, in this case, is the element of work that requires interpersonal interaction to carry a task or job (Charbonnier‐Voirin & Roussel, 2012; Michael; Sony & Mekoth, 2014). The interpersonal element may vary depending upon the three types of integration due to the implementation of Industry 4.0. The vertical integration in Industry 4.0 (Y. Chen, 2017), may warrant frequent digital and physical interaction with employees from another department within the same organization to carry out one’s task. To cite an instance of frequent interaction between design and marketing departments. Therefore, employees will have to adjust their interpersonal style of work with other employees. The philosophical principles behind vertical integration in Industry 4.0 are to bring in transparency, sharing of information and cooperative decision making to meet organizational goals (Liao et al., 2017; Michael; Sony, 2018). To achieve this goal the employees need to collaborate and with employees from other departments within the organization to carry out one’s work to meet the overall goals of vertical integration (Spasojevic Brkic et al., 2020). The success of vertical integration will provide the opportunity for employees from different departments, to communicate and carry out the task in a cooperative, collaborative manner on common goals or objectives of the organization (Wrede et al., 2016). This is possible if employees understand other points of view. Hence it would be one of the critical factors for employees to adapt to one’s job. The dynamics of vertical integration will also result in social actions that characterise the interactions of knowledge between various entities within the value chain in the organization (Michael Sony & Naik, 2019b). So, there will be difficulty in transferring information into codes previously shared (Ahmad et al., 2017) with actors within the value chain within the organization. Hence, interpersonal knowledge sharing in terms of a pack of codes will contribute to the social dynamics of interpersonal interaction warranting employees to adapt by taking into consideration these social dynamics. The horizontal integration was intended in principle in Industry 4.0 to integrate the value chains or supply chains external to the organization digitally to achieve the overall goals of the value or supply chain (Sony & Aithal, 2020a). Therefore, in horizontal integration, the various partners in the chain are held together by the strategy of cooperative success and not entirely by ownership (Sony & Aithal, 2020a). Hence, this will lead to powerful integration with retailers, suppliers, data sharing, human resources, capital, knowledge and skills etc (Saldivar et al., 2015). It will further result in employees changing one’s work practices depending on the requirements of other partnering organizations (Lent, 2018). The tendency to continuously learn from other people will also be imperative for the adaptability of employees. The tendency to consider the point of view of other partnering organization employees and convincing employees on the work practices will benefit the whole supply chain. Such a skill will be the most substantial interpersonal skill for employees in the Industry 4.0 era. The end-to-end integration is a new paradigmatic shift that will result in the integration of activities along the product life cycle. This is intended to extend the value chain through to the customer and will be a significant element for customer management. The concept of product-to-service integration will be made a reality by end-to-end integration (Chen, 2017). The employees will, therefore, need to deal with customer needs throughout the stage of a product life cycle. The online monitoring of data usage of the product will require employees to interpersonally persuade customers for various solutions. To cite an example, online monitoring of car engine performance, if the employee detects some abnormality even before any noticeable effects are noted by the user, it will be challenging to convince the user for the solutions, as he may feel his car is ok (Sony & Aithal, 2020a). This will warrant an employee to adapt his interpersonal styles depending upon the situation.

4.2. Dealing with crises and unforeseen circumstances adaptability in Industry 4.0

In the seminal work by Pulakos et al. (2000) the ability of the employees to deal with an emergency or an unexpected circumstance will be an important factor for employee adaptability. They had proposed two dimensions i.e. adaptability to deal with emergencies and dealing with uncertain & unpredictable work situations in their generalised model of employee adaptability. Subsequently, Charbonnier‐Voirin and Roussel (2012) combined both these dimensions, i.e., reactivity in the face of emergencies or unexpected circumstances suggesting the importance of this dimension in employee adaptability. The three forms of integration in Industry 4.0 will demand employees to deal with crises and unforeseen circumstances. The vertical integration in Industry 4.0 will result in the seamless integration of hierarchical levels with the exchange of data, capital and resources (Chen, 2017; Dengler & Matthes, 2018). For instance, a risky situation in one department e.g. data theft or a cybersecurity issue (Sony & Aithal, 2020a; Thames & Schaefer, 2017) will now have repercussions in all other departments because by vertical integration all departments are interconnected. From a pragmatic perspective, the challenge is complex because employees need to apply their skills, strategies, and tools to solve the problem at hand. The horizontal integration leads to interconnectivity among the supply chain partners and hence any emergency or dangerous situation will warrant employee’s all along the supply chain to handle the same. In the end-to-end integration, the product usage along different phases of the product life cycle can result in crises or emergencies or unforeseen circumstances or risks. For example, product failure or malfunction in the customer’s hands will create crises or unforeseen circumstances and employees will have to aptly handle an event. Therefore, the implementation of Industry 4.0 will require employees to deal with emergencies and unexpected circumstances.

4.3. Adaptability to creative problem-solving in Industry 4.0

Every employer looks for an employee who can solve problems in an organization (Velury, 2005). The standardised and manual jobs are automated with the implementation of Industry 4.0. The shift will lean towards knowledge-based and higher qualified jobs (Bonekamp & Sure, 2015). The routine problem solving will be automated and what remains for the employees in the era of Industry 4.0 are problems that are new or ill-defined (Frey & Osborne, 2017; Schneider, 2018). Depending on the context of work and the occurrence of such problems will vary in organizations. Hence, the employee will need the ability to identify the problem correctly and mitigate the same with suitable solutions, appropriate for the context of the application. Due to vertical integration, the different departments are digitally integrated; therefore, solving problems will require employees to possess a multi-disciplinary perspective. Employees need to also study the impact of problem-solving on another department. Therefore, the solution will be required to satisfy the constraints of all other participating departments within the organization. Another challenge would be that when the problem is complex and ill-defined as in the case of Industry 4.0, and the creative employees may be in a better position to solve it (Gryazeva-Dobshinskaya et al., 2018; Newman, 2017).

The horizontal integration in Industry 4.0 also makes most problems will be multi-organizational. Hence, there will be multi-objective and multiple constraints that are specific to each organization and which will have binding constraints on the other. Likewise, while solving such problems the strategic intention of all the collaborating organizations in the value or supply chain should not be disturbed. The solutions to these problems will have to be implemented by more than one organization (Sony & Aithal, 2020b). The end-to-end integration will result in a large amount of data that will have to be collected, collated and analysed to solve a problem. The creative analysis of the data will create insights for problem-solving. In addition to that, solving such problems may also lead to create new business opportunities and maintain existing strategies. Some of the skills an employee may require for creative problem solving are research, analysis, decision making, thinking out of the box, communication. Also, employees should find a solution in a timely and cost-efficient manner. Hence, the creative problem-solving ability will be the most important thing for employees to solve such complex problems due to the implementation of Industry 4.0 (Shamim et al., 2016).

4.4. Adaptability with continuous learning, training, and education in Industry 4.0

The jobs due to the implementation of Industry 4.0 tends to be complex (Sony, 2020). The tasks or duties carried out by the employees in the Industry 4.0 era will undergo a drastic change (Nedelkoska & Quintini, 2018). The technical systems in Industry 4.0 are constantly changing (Gehrke et al., 2015; Hecklau et al., 2016). Hence, the employees will continuously indulge in learning, training, and education (Bode et al., 2018; Störmer et al., 2014). Another interesting skill set that almost every discipline will need is the ICT skill. In almost all the disciplines there is a polarisation towards information technology and artificial intelligence (Hirsch-Kreinsen, 2014; Wulfken & Müller, 2017). Therefore, employees will have to be updated on these skills. Industry 4.0 will cast the onus of productivity on the employees. It will be their responsibility to continuously train, educate and retrain (Wulfken & Müller, 2017). The employee who learns these skills promptly will adapt (Sony & Naik, 2020a). All three forms of integration in Industry 4.0 will need employees to be acquainted with skills from other departments or organizations. Consequently, employees will have to continuously unlearn, learn, train and educate themselves in related cross disciplines (Schallock et al., 2018), in an autonomous and self-regulating manner (Adam et al., 2019) to be employable. Furthermore, the awareness of various skills and evaluating these skills concerning oneself and taking appropriate actions to acquire skills will be a significant factor in employee adaptability. Due to integration in Industry 4.0, the employees will have to learn, train and educate themselves in a large repertoire of skills (Michael Sony & Naik, 2019a). To cite an example employees in manufacturing will have to learn about customer relationship management skills. Therefore, in the Industry 4.0 era continuous learning, training and education will be explicitly stated in their job profiles.

4.5. Adaptability with managing stress in Industry 4.0

Modern working conditions in the Industry 4.0 era is changing drastically due to digitalisation (Sony, 2018). One of the characteristics of the era would be the high degree of human-machine interaction (HMI; Sony & Naik, 2019a). A higher degree of HMI may impact the employees at both physical and psychosocial levels (Körner et al., 2019; Wixted et al., 2018). Likewise, the highly automated environment will increase the mental workload (Körner et al., 2019). This is due to technical problems, poor usability, low situation awareness and an increased requirement on employees’ qualifications. Technical problems such as breakdown or slowdown were the major stressors when employees were not qualified to attend those (Körner et al., 2019). Another fact is that the employees in such an environment are cognitively overloaded. This is because of the high level of supervisory monitoring of highly complex and automated systems (Berg et al., 2018; Wixted et al., 2018). Vertical integration in Industry 4.0 will result in the integration of various functional departments in the organization (Sony & Aithal, 2020a). Every department, in the organization, wants to maximise their interest. To attain collaboration and cooperation of these departments could be a major source of stress for the employees (Hirschi, 2018). In horizontal integration, the partnering organization external to the organizations will have their vested objectives. Seeking collaboration and cooperation of all partnering organizations could also be a major source of stress. In end-to-end integration technical aspects such as machine to machine integration, customer needs analysis, product-to-service integration (Chen, 2017) may demand colossal cognitive skill requirements, which will further compound the employee stress. The employees in all three forms of integration will be dependent on technology to achieve organisational goals, perform tasks, and ultimately transform work patterns (Graetz & Michaels, 2018). Industry 4.0 uses technology to extend the capabilities of employees. The extension of these capabilities is not infinite, and once the optimum level is crossed it will result in system feature overload, information overload, and communication overload (Karr-Wisniewski & Lu, 2010). Employees using such a system will be overloaded. Employees who learn to manage this stress will be effective in adapting to Industry 4.0.

4.6. Team adaptability in Industry 4.0

An effective team is one of the key elements for the success of any organization. The working teams in the modern era have become complex (Mathieu et al., 2018). The traits of an effective team are that it is self-correcting, adaptable, flexible, and cohesive. Another feature is that effective teams hold shared mental models of their tasks, objectives and teammates (DeChurch & Mesmer-Magnus, 2010; Driskell et al., 2018). Most of the work in the Industry 4.0 era is done by teams or groups (Gryazeva-Dobshinskaya et al., 2018). These teams are not only for problem-solving but also for executing other functions of management such as planning, leading, organising, and controlling. Each employee will use their unique and shared knowledge to create a common outcome collaboratively to meet the goals of the organization. The typical knowledge activities in a team would be knowledge acquisition, knowledge sharing, knowledge combination, knowledge creation, knowledge application and knowledge revision (Jackson et al., 2006). A team will comprise of individuals which are specializing in a specific Industry 4.0 technology. Besides, in the companies, there are domain experts who have extensive knowledge about their operations. Thus, the team will comprise specific domain experts and experts from other functional areas. Though the knowledge should be shared among the team, however, the onus of execution would lie on the domain experts after getting collaborative inputs from all the members of the team. Another point to consider is that in Industry 4.0 the data scientists and manufacturing people should work together to create better artificial intelligence algorithms, which will help in operations and maintenance decisions in an organization (Subramaniyan et al., 2020). In addition, the different functional departments within an organization will work as a team due to vertical integration in Industry 4.0. Each important project or task will comprise of a separate team because conventional hierarchal structures will be dissolved (Bonekamp & Sure, 2015; Fettig et al., 2018). In a survey conducted among the representatives of Industry, it was found that teamwork will be more significant in Industry 4.0 (Bonekamp & Sure, 2015). Horizontal integration in Industry 4.0 will cause the teams external to the organization and within the partnering organization to work together for carrying out a specific task or activity. For the success of horizontal integration, teams from different partnering organizations with different organizational cultures (Sony, 2018; Sony & Aithal, 2020b) should adapt and work together cohesively to achieve common objectives (Sony & Aithal, 2020a). When there are elements from different organizational cultures, special efforts will have to make to be cohesive and effectively work towards the common objectives of horizontal integration in Industry 4.0. The end-to-end integration teams will be formed in different phases of the product life cycle. A typical team in this phase would be technical engineers or analysts, customer needs analysts, product to service teams. Working in teams will be central for working in an Industry 4.0 environment; therefore, employees will have to adapt to both in-role behaviours and extra-role behaviours (Palazzeschi et al., 2018) while working in teams. The in-role team behaviours are those which are prescribed as a part of their job description. The extra-role behaviours are not part of their job description, but these behaviours are essential and contextual behaviours that are essential for the success of Industry 4.0 teams. Therefore, team adaptability in Industry 4.0 context is complex and multi-dimensional.

4.7. Interaction of the proposed dimensions

The proposed six dimensions of the construct of employee adaptability will have an interactive effect among them. To cite an instance the ability of the employee to adapt to creative problem-solving in Industry 4.0, will interact with the ability to manage stress, and team adaptability. This depicts that employees should adapt equally in all the dimensions and failure to adapt to any of these dimensions will not only impact the concerned dimension but also other dimensions. Therefore, it depicts the significance for employees to adapt to each of these dimensions.

4.8. Ranking of employee adaptability dimensions

To rank the employee adaptability dimensions unearthed in the systematic literature review, the perceptions of senior human resource managers of manufacturing industries, who implemented Industry 4.0 were considered. The objective was to find the degree to which each employee adaptability factor was considered critical. A survey questionnaire was emailed to 120 senior managers from manufacturing Industries in India. Each of the adaptability factors was given a brief description and a five-level rating scale ranging from critical for success to neither critical nor important was furnished. The numerical rating scheme is tabulated in Table 1.

Table 1. Ranking of Critical Success Factors

Adaptability factors	Extremely critical and important for success (rating 5)	Critical and important for success (rating 4)	Somewhat critical and important for success (rating 3)	Important but not critical for success (rating 2)	Neither critical and nor important for success (rating 1)	Total Score	Average	Normalisation
Adaptability with continuous learning, training, and education in Industry 4.0	35.00	12.00	5.00	4.00	2.00	248.00	4.28	1.00
Interpersonal Adaptability in Industry 4.0	31.00	16.00	4.00	4.00	3.00	242.00	4.17	0.73
Team Adaptability in Industry 4.0	28.00	14.00	12.00	3.00	1.00	239.00	4.12	0.59
Adaptability to creative problem solving in Industry 4.0.	26.00	14.00	13.00	2.00	3.00	232.00	4.00	0.27
Dealing with crises and unforeseen circumstances adaptability in Industry 4.0	26.00	15.00	8.00	5.00	4.00	228.00	3.93	0.09
Adaptability with managing stress in Industry 4.0	2.00	14.00	8.00	10.00	1.00	226.00	3.90	0.00

A total of 62 responses was received. Four of the responses were incomplete and hence were discarded. A total of 58 valid responses were considered. The response rate was 48%. Surveys with response rates greater than 30% are considered acceptable (Easterby-Smith et al., 2012). Table 1 depicts the ranking of these factors. The most critical factor for the success of Industry 4.0 was adaptability with continuous learning, training and education and least. To find the critical factor for employee adaptability for Industry 4.0 success, we used a methodology suggested by Adabre and Chan (Adabre & Chan, 2019). The normalised mean was calculated as Normalized = (mean – minimum mean)/(maximum mean – minimum mean). The normalised score greater than 0.5 was considered a critical employee adaptability factor for the success of Industry 4.0. The three dimensions of employee adaptability are adaptability with continuous learning, training and education in Industry 4.0, interpersonal adaptability in Industry 4.0 and team adaptability. To survive in the modern market, irrespective of the sector the employees need to add value beyond what can be performed by automated systems and connected & intelligent machines, also operate in the digital environment and continuously adapt to new ways of working and new occupations (Marco et al., 2021). Thus, the skill of adaptability with continuous learning, training and education in Industry 4.0 will help the employees to continuously adapt to new ways of working and new occupations and operate in a digital environment. This is because of new skill set that an employee will acquire through learning, training, and education about digital technologies will be a useful hard skill to acquire. Hence, these are the most critical skills for employee adaptability for the success of Industry 4.0. The other two critical skills being interpersonal adaptability in Industry 4.0 and team adaptability are soft skills. These skills being non-technical are much harder to replicate via automation and AI. Therefore, it will be the other two most critical employee adaptability skills for the success of Industry 4.0. In a study by Mc Kinsey, wherein they studied 10.2 million job postings from 2017 to 2019 to analyse how return on skills has shifted. They found that soft skills communication and teamwork, two perennial skills useful for most jobs (Avrane-Chopard & Potter, 2019). This study also rightly finds the importance of these two skills for the success of Industry 4.0.

5. Proposed conceptual model

The successful implementation of Industry 4.0 will result in three types of integration the vertical, horizontal, and end-to-end integration(Wang et al., 2016). The three types of integration will help to implement the front end technologies such as smart supply chain, smart working, smart manufacturing and smart products (Frank et al., 2019). The degree of implementation of these technologies will vary in organizations (Dalenogare et al., 2018) and for that reason, the challenges the employees face in the organizations may differ. An employee will adapt to the six dimensions found in this study. Thus, the proposed framework will have Industry 4.0 integration as a central concept. The proposed six dimensions of employee adaptability are in the second layer.

Industry 4.0 employees are knowledge employees; therefore, they should autonomously manage themselves along these six dimensions and hence one of the components of the third layer is autonomously managing oneself. The third layer also suggests that employees should indulge in self-examination and self-awareness on each of the six dimensions in a continuous manner and is depicted in Figure 1. This is because the challenges of Industry 4.0 will vary longitudinally. In terms of organization, the feedbacks on each dimension of adaptability should be analysed, and each employee should be frequently apprised about it using HR analytics continuously. Specific training modules in each of the dimensions should be imparted to employees as and when the need arises. Organizations should understand the importance of each of the adaptability dimensions. As non-adaptability in any one of these dimensions due to interactive effect may have an impact on the other dimension. However, a point to be stressed is that the most critical dimensions of employee adaptability that are depicted in boxes are shown in red colour should be the first ones the organization should concentrate on building in the employees. However, the other ones in green should also be developed in the due course.

Figure 1. Proposed Conceptual Model of Employee Adaptability in Industry 4.0.

6. Discussion

Employees are pivotal for the successful implementation of Industry 4.0 (Bonekamp & Sure, 2015; Sony & Aithal, 2020a). This study unearthed six dimensions of employee adaptability skills for the successful implementation of Industry 4.0. These six dimensions are generic and can be applied across the sectors. The proposed model extends the research of employee adaptability in an Industry 4.0 setting. The Industry 4.0 employees are knowledge workers (Nellemann & Pedersen, 2019); hence, employees need to develop these adaptability skills through self-awareness, self-analysis, feedback analysis along with managing oneself and being autonomous. Thus, employee adaptability in the Industry 4.0 era will be the responsibility of both employees and the organization (Lepore et al., 2021; Ravina-Ripoll et al., 2019; Sony & Aithal, 2020a). The employees need to inculcate these Industry 4.0 skills rapidly, else, it would make them redundant (Bonekamp & Sure, 2015; Brkic et al., 2019). The three most critical skills should be acquired by the employees, as it will help them to be adaptable in the new Industry 4.0 environment. The self -examination, self-awareness & feedback analysis should be proactively used by the employees to concentrate on these most critical employee adaptability dimensions. Subsequently, the other three dimensions should also be acquired, and not neglected as these dimensions are interrelated. The organizations should also systematically train the employees in these employee adaptability dimensions in a strategic manner (Clarizia et al., 2021; Fitsilis et al., 2018). The first step the organizations should take is to assess employee adaptability along these six dimensions. Of these, the three critical employee adaptability dimensions should be given the top priority and a strategic intervention mechanism should be devised. The dimensions in which the employees score less than the benchmark, the organization will have to explain to the employee and design intervention strategies to improve the adaptability of employees in these dimensions. The dimensions in which the scores of employee adaptability are acceptable, the employees should be apprised about it, commended and motivated either financially or non-financially and design intervention strategies to sustain the performance. The proposed framework of the Industry 4.0 employee adaptability model, thus can be used by both employees and organizations to improve employee adaptability.

7. Limitation and future research direction

The review was restricted by the database access, the search criteria employed in this research, inclusion, and exclusion criteria. Besides, the conceptual model is constructed using deductive methodology using the existing literature by grouping the six constructs of employee adaptability. This model should be verified through an empirical study. The first step would be to conduct a qualitative study to verify whether these dimensions of adaptability. Besides, it will also allow adding or deleting any dimensions of employee adaptability. The sector-wise qualitative study will help to unearth any sector-specific impact on these dimensions. The second step would be to develop a scale of employee adaptability. This will help the organizations and employees to use a statistically validated scale to measure employee adaptability. Future studies should also explore curriculum development for training employees in the employee adaptability dimensions. Another future direction is to study the same problem through empirical research (inductive) and build a framework and compare it with the proposed framework. This might explain the gaps between the research and practice and enrich the current framework with empirical insights.

8. Conclusion

Industry 4.0 represents the digital transformation of modern-day organizations to meet the organization goals and objectives using advances in ICTs such as IoT, cloud computing and Big Data. Industry 4.0 is a socio-technical phenomenon and hence the role of employees in the successful implementation of Industry 4.0 is pivotal. This study through a systematic literature review explored the six dimensions on which the employees must adapt for the successful implementation of Industry 4.0. The six dimensions unearthed in this study are interpersonal Adaptability in Industry 4.0, dealing with crises and unforeseen circumstances adaptability in Industry 4.0, adaptability to creative problem-solving in Industry 4.0, adaptability with continuous learning, training, and education in Industry 4.0, adaptability with managing stress in Industry 4.0 and team Adaptability in Industry 4.0. The conceptual model of employee adaptability was constructed using these constructs.

Acknowledgments

We thank the anonymous reviewers for the constructive suggestion that we believe has improved the quality of the paper. We are also thankful to the editorial team for all the guidance.

Disclosure statement

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

Appendix A:

Search String

Table

Part 1	Part 2
Industry 4.0 Or Industrie 4.0 Or The fourth industrial revolution Or The 4^th industrial revolution Or Smart manufacturing Or Smart Factory Or Smart factories Or Cyber physical system Or Cyber physical production system Or CPS Or Internet of things Or Industrial Internet Or Big data Or Digitization Or Digitization Or Digitilisation Or Digitisation	Employees Adaptability Or Adaptive Performance Or Human Resources Or People Or Employee Skills Or Employee Ability Or Knowledge society