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The service recovery literature provides little guidance to firms on how users of self-service technology (SST) perceive assistance provided by human and non-human service agents following a service obstacle. This research responds by addressing two important research questions about SST recovery: (1) how are perceptions of assistance provided following a service obstacle influenced by a customer's psychological needs? and (2) does supporting the psychological needs of customers positively impact continuance intentions following a service obstacle?

Data are collected to address the research questions via five experiments that explore how assistance provided by a non-human (vs human vs no assistance) service agent contributes to perceptions of psychological support and continuance intentions following a service obstacle while volitionally using SST.

The results show that while users of SST would prefer to do so without an obstacle requiring intervention of a service agent, if assistance is required then the psychological need support elicited from a non-human service agent was vital to an effective recovery. Further, the findings highlight some boundary conditions for this relationship, with the impact of customer perceived need support on continuance intentions found to be sensitive to fit between the task and assistance provided and the complexity of the task being completed.

Much of the prior service recovery literature has emphasized the different types of tactics that can be used (e.g. apologizing, monetary compensation and explaining what happened), failing to appreciate the role of different types of service agents or the underlying psychological process that explain the relative merit of such tactics. The present research shows that for these tactics to influence continuance intentions, they must be provided by a relevant service agent and support a customer's psychological need for autonomy, competence and relatedness. The hypothesized impact of psychological need support on continuance intentions was also observed to be contingent upon the fit between the task and the type of assistance provided, where the level of task complexity attenuated this fit.

Blockchain for energy trading is a trending research area in the current context. However, a noticeable gap exists in the review articles focussing on solar energy trading with blockchain technology. Thus, this study aims to systematically examine and synthesise the existing research on implementing blockchain technology in sustainable solar energy trading.

The study pursued a systematic literature review to achieve its aim. The data extraction process focussed on the Scopus and Web of Science (WoS) databases, yielding an initial set of 129 articles. Subsequent screening and removal of duplicates led to 87 articles for bibliometric analysis, utilising VOSviewer software to discern evolutionary progress in the field. Following the establishment of inclusion and exclusion criteria, a manual content analysis was conducted on a subset of 19 articles.

The results indicated a rising interest in publications on solar energy trading with blockchain technology. Some studies are exploring the integration of new technologies like machine learning and artificial intelligence in this domain. However, challenges and limitations were identified, such as the absence of real-world solar energy trading projects.

This study offers a distinctive approach by integrating bibliometric and manual content analyses, a methodology seldom explored. It provides valuable recommendations for academia and industry, influencing future research and industry practices. Insights include integrating blockchain into solar energy trading and addressing knowledge gaps. These findings advance societal goals, such as transitioning to renewable energy sources (RES) and mitigating carbon emissions, fostering a sustainable future.

Both technological and human-centric perspectives need to be acknowledged when combining lean production practices and Industry 4.0 (I4.0) technologies. This study aims to explore and explain how lean production practices and I4.0 technologies may coexist to enhance the human-centric perspective of manufacturing operations in the era of Industry 5.0 (I5.0).

The research approach is an explorative and longitudinal case study. The qualitative data collection encompasses respondents from different job functions and organizational levels to cover the entire organization. In total, 18 interviews with 19 interviewees and five focus groups with a total of 25 participants are included.

Identified challenges bring forth that manufacturing organizations must have the ability to see beyond lean production philosophy and I4.0 to meet the demand for a human-centric perspective in socially sustainable manufacturing in the era of Industry 5.0.

The study suggests that while lean production practices and I4.0 practices may be considered separately, they need to be integrated as complementary approaches. This underscores the complexity of managing simultaneous organizational changes and new digital initiatives.

The research presented illuminates the elusive phenomena comprising the combined aspects of a human-centric perspective, specifically bringing forth implications for the co-existence of lean production practices and I4.0 technologies, in the transformation towards I5.0.

The study contributes to new avenues of research within the field of socially sustainable manufacturing. The study provides an in-depth analysis of the human-centric perspective when transforming organizations towards Industry 5.0.

This study aims to gain insights into the rise of virtual social media influencers and identify the significant theories governing virtual influencers’ (VIs) interaction with followers on social media platforms. Studies on VI being scarce in marketing literature, the authors attempt to propose a theoretical model to understand the acceptance of VIs by social media users (SMUs).

Using a structured literature review and a case study approach, a conceptual model is developed and propositions are offered.

Parasocial interaction (PSI) between the SMU and VIs builds up source credibility, thereby leading to the acceptance of VIs. Thus, the authors establish that PSI and source credibility theory combine to explain the acceptance of VIs by SMUs. Furthermore, similarity with the VI is another added dimension of source credibility, as suggested by this study. A comparative analysis of the growth of five major VIs elucidates that the fashion, electronic, tourism and health-care industries can use them for promotions and as influencers, especially for luxury products.

VIs are a potent tool to achieve improved brand awareness and to target young consumers (especially Gen Y and Gen Z – millennials).

The emergence of VIs being recent; little is comprehended about their interaction with SMUs. Hence, it becomes important to delineate the foundations of VI–SMU interaction. Thus, this study addresses the gap in identifying the theoretical background and proposes a conceptual model elucidating VI acceptance by SMUs.

The purpose of this paper is to investigate the research landscape of LSS 4.0 papers published in two well-known repositories, Scopus and Web of Science (WoS), in terms of publication trends, article distribution by author, journal, affiliations and country, and article clustering based on keywords, authors and countries. In addition, a literature review was carried out to build a conceptual framework of integrated Lean Six Sigma and Industry 4.0 (LSS 4.0) that encompasses operational, sustainability and human factors or ergonomics aspects.

The literature review of integrated Lean Six Sigma and I4.0 publications published in Scopus and WoS databases in the current decade was conducted for the present study. This study categorizes LSS, I4.0 and related research articles based on publication patterns, journals, authors and affiliations, country and continental-wise distribution and clustering the articles based on keywords and authors from the Scopus and WoS databases from 2011 to 2022 using the search strings “Lean”, “Six Sigma”, “Lean Six Sigma” and “Industry 4.0” in the Title, Abstract and Keywords using Biblioshiny, VOS viewer and Microsoft Excel.

In the recent three years, from 2020 to 2022, LSS 4.0 has been substantially increasing and is seen as an emerging and trending area. This research identifies the most influential authors, most relevant affiliations, most prolific countries and most productive journals and clusters based on keywords, authors and countries. Further, a conceptual framework was developed that includes the impact of operational, sustainability and ergonomic or human factors in LSS 4.0.

This article assists in comprehending the trends and patterns of LSS 4.0. Further, the conceptual framework helps professionals and researchers understand the significance and impact of integrating LSS and Industry 4.0 in the aspects of human factors/ergonomic, sustainability and operations. Also, the research induce professionals to incorporate all these factors while designing and implementing LSS 4.0 in their organization.

This conceptual framework and bibliometric analysis would aid in identifying potential areas of research and providing future directions in the domain of LSS 4.0. It will be beneficial for academicians, professionals and researchers who are planning to apply and integrate techniques of LSS and technologies of I4.0 in their organizations and research.

The study proposes to determine the impending challenges to lean integration with Industry 4.0 (I4.0) in manufacturing that aims at achieving desired operational performance. Integrating lean and Industry 4.0 as the two industrial approaches is synergetic in providing operational benefits such as increasing flexibility, improving productivity, reducing cost, reducing delivery time, improving quality and value stream mapping (VSM). There is an urgent need to understand the integrated potential of OPEX strategies like lean manufacturing and also to determine the challenges for manufacturing SMEs and further suggest a strategic roadmap for the future.

The current work has used a combined approach on interpretative structural modeling (ISM) and fuzzy Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) approach to structure the multiple level analysis for the implementation challenges to integrate OPEX strategies with Industry 4.0.

The research has found that the indulgence of various implementation issues like lack of standardization, lack of vision and lack of trained support, all are the major challenges that inhibit the integration of OPEX strategies with I4.0 technologies in manufacturing.

The research has investigated the internal factors acting as a roadblock to lean and Industry 4.0 adoption. Further studies may consider external factors to lean and Industry 4.0 implementation. Also, further research may consider other operational excellence approaches and extend further to relevant sectors.

This study provides the analysis of barriers that is useful for the managers to take strategic actions for implementing OPEX strategies with I4.0 in smart manufacturing.

The research determines the adoption challenges towards the integrated framework. This is the first study to explore challenges in integrating OPEX strategies with I4.0 technologies in manufacturing SMEs.

This study investigates the integration of Industry 4.0 (I4.0) technologies with condition-based maintenance (CBM) in upstream oil and gas (O&G) operations, focussing on developing countries like Nigeria. The research identifies barriers to this integration and suggests solutions, intending to provide practical insights for improving operational efficiency in the O&G sector.

The study commenced with an exhaustive review of extant literature to identify existing barriers to I4.0 implementation and contextualise the study. Subsequent to this foundational step, primary data are gathered through the administration of carefully constructed questionnaires targeted at professionals specialised in maintenance within the upstream O&G sector. A semi-structured interview was also conducted to elicit more nuanced, contextual insights from these professionals. Analytically, the collected data were subjected to descriptive statistical methods for summarisation and interpretation with a measurement model to define the relationships between observed variables and latent construct. Moreover, the Relative Importance Index was utilised to systematically prioritise and rank the key barriers to I4.0 integration to CBM within the upstream O&G upstream sector.

The most ranked obstacles in integrating I4.0 technologies to the CBM strategy in the O&G industry are lack of budget and finance, limited engineering and technological resources, lack of support from executives and leaders of the organisations and lack of competence. Even though the journey of digitalisation has commenced in the O&G industry, there are limited studies in this area.

The study serves as both an academic cornerstone and a practical guide for the operational integration of I4.0 technologies within Nigeria's O&G upstream sector. Specifically, it provides an exhaustive analysis of the obstacles impeding effective incorporation into CBM practices. Additionally, the study contributes actionable insights for industry stakeholders to enhance overall performance and achieve key performance indices (KPIs).

Prior to managing a company’s processes in the presence of a combination of paradigms, there is a need to understand their underlying interaction. This paper systematically reviews the existing literature that discusses the interaction between lean production (LP) and the fourth industrial revolution (i.e. Industry 4.0). The study aims to understand how the interaction unfolds and whether it is synergistic.

The research relies on a systematic literature review of peer-reviewed articles from Scopus and Web of Science that discuss the interaction between the two paradigms. The final set of articles pertaining to the topic was analysed.

The article presents that the interaction between the two paradigms occurs through a representation of the pillars of the House of Lean (HoL) interacting with the nine technological pillars of Industry 4.0. There is a consensus on the synergistic nexus among the pillars and their positive impact on operational performance. We also demonstrate the weights of the interactions between the two paradigms and the areas of operations management where this interaction takes place through Sankey charts. Our research indicates that the largest synergistic interaction occurs between just-in-time and industrial Internet of Things (IIoT) and that companies should invest in IoT and cyber-physical systems as they have the greatest weight of interactions with the pillars of the HoL.

This research facilitates a deeper insight into the interaction between LP and Industry 4.0 by organising and discussing existing research on the subject matter. It serves as a starting point for future researchers to formulate hypotheses about the interaction among the various pillars of LP and Industry 4.0, apply these interactions and test them through empirical research.

It could serve as a guide for managers to understand with which interactions they should start the digitalisation process.

With the rise in discussions on the interaction between the two paradigms, there is still an opportunity to understand the specificity of this interaction. Compared to the initial seminal works on the subject, such as Buer et al. (2018b), which investigated the direction of interaction between the two paradigms, this research contributes to further investigating this specificity and gaining a better understanding of the relationship governing the interaction between LP and Industry 4.0 by delineating the interaction state among the pillars of the two paradigms and its relevant importance.

Digital lean implementation can solve the dual problem of stagnating quality and rising costs in healthcare. Although technology adoption in healthcare has increased in the post-COVID world, value unlocking using technology needs a well-thought-out approach to achieve success. This paper provides a prescriptive framework for successfully implementing digital lean in healthcare.

This study uses a mixed-method approach to achieve three research objectives. Whilst it uses a narrative review to identify the enablers, it uses qualitative thematic analysis techniques to categorise them into factors. The study utilises the delphi method for the thematic grouping of the enablers in the broader groups. The study used an advanced ordinal priority approach (OPA) to prioritise these factors. Finally, the study uses concordance analysis to assess the reliability of group decision-making.

The study found that 20 identified enablers are rooted in practice factors, followed by human resource management (HRM) factors, customer factors, leadership factors and technology factors. These results further counter the myth that technology holds the utmost significance in implementing digital lean in healthcare and found the equal importance of factors related to people, customers, leadership and best practices such as benchmarking, continuous improvement and change management.

The study is the first of its kind, providing the prescriptive framework for implementing digital lean in healthcare. The findings are useful for healthcare professionals and health policymakers.

Modern subway transportation systems need to satisfy increasing safety demands to rapidly evacuate passengers under hazardous emergency circumstances, such as fires, accidents or terrorist attacks, to reduce passenger injuries or life losses. The emergency evacuation capacity (EEC) of a subway station needs to be revised timely, in case passenger demand increases or the evacuation route changes in the future. However, traditional ways of estimating EEC, e.g. fire drills are time- and resource-consuming and are difficult to revise from time to time. The purpose of this study is to establish an intuitive modelling approach to increase the EEC of subway stations in a stepwised manner.

This study develops an approach to combine agent-based evacuation modelling and building information modelling (BIM) technology to estimate the total evacuation time of a subway station.

Evacuation time can be saved (33% in the studied case) from iterative improvements including stopping escalators running against the evacuation flow and modifying the geometry around escalator exits. Such iterative improvements rely on integrating agent-based modelling and BIM.

The agent-based model can provide a more realistic simulation of intelligent individual movements under emergency circumstances and provides precise feedback on locations of evacuation bottlenecks. This study also examined the effectiveness of two rounds of stepwise improvements in terms of operation or design to increase the EEC of the station.