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The purpose of this paper is to investigate and quantify the impact of product complexity, including architectural complexity, on operator learning, productivity and quality performance in both assembly and disassembly operations. This topic has not been extensively investigated in previous research.

An extensive experimental campaign involving 84 operators was conducted to repeatedly assemble and disassemble six different products of varying complexity to construct productivity and quality learning curves. Data from the experiment were analysed using statistical methods.

The human learning factor of productivity increases superlinearly with the increasing architectural complexity of products, i.e. from centralised to distributed architectures, both in assembly and disassembly, regardless of the level of overall product complexity. On the other hand, the human learning factor of quality performance decreases superlinearly as the architectural complexity of products increases. The intrinsic characteristics of product architecture are the reasons for this difference in learning factor.

The results of the study suggest that considering product complexity, particularly architectural complexity, in the design and planning of manufacturing processes can optimise operator learning, productivity and quality performance, and inform decisions about improving manufacturing operations.

While previous research has focussed on the effects of complexity on process time and defect generation, this study is amongst the first to investigate and quantify the effects of product complexity, including architectural complexity, on operator learning using an extensive experimental campaign.

Online shopping around the world is growing exponentially, especially during the COVID-19 pandemic. This study aims to examine how an online customer's purchasing experience influences his/her buying intention and willingness to believe in fraud news, as well as the ripple impact of satisfaction and trust, with gender as a moderator in an emerging economy during COVID-19.

Based on the underpinning of the stimulus-organism-behavior-consequence (SOBC) theory, the research model was developed, and collected data from 259 respondents using convenience samples technique. Next, the data were analyzed using partial least squares-based structural equation modeling (PLS-SEM), SPSS (Statistical Package for the Social Sciences) and Hayes Process Macro.

The study results confirmed that the online shopping experience (OSE) has positive impact on customers' satisfaction (CS), purchase intention (PI) and customer trust (CT); CS has positive effects on trust toward online shopping and their future product PI; future product PI significantly affects customers' propensity to believe and act on fraud news (PBAFN). The finding also states that gender moderates the relationships of CS to PI, OSE to PI and PI to PBAFN, but doesn't moderate the CT to PI relationship.

The study findings will assist policymakers and online vendors to win customers' hearts and minds' through confirming satisfaction, trust and a negative attitude toward fake news, which will lead to customer loyalty and the sustainable development of the industry. Finally, the limitations and future research directions are discussed.

Since Industry 4.0 (I4.0) is a new idea in Bangladesh, this study supports I4.0 adoption. Companies struggle to implement I4.0 and fully profit from the fourth industrial revolution’s digital transformation due to its novelty. Although barriers to I4.0 adoption are thoroughly studied, the literature has hardly examined the many aspects that are crucial for I4.0 adoption in Bangladesh’s Ready-Made Garment (RMG) industry. So, the purpose of this study is to investigate the barriers of adopting I4.0 in relation to Bangladesh’s RMG industries to enhance the adoption of I4.0 by developing a framework. Ultimately, the goal of this research is to improve the adoption of I4.0 in Bangladesh.

Through a comprehensive analysis of the existing research, this paper aims to reveal the barriers that must be overcome for I4.0 to be adopted. For evaluating those barriers, a decision analysis framework based on the combination of Delphi technique and Decision-Making Trial and Evaluation Laboratory (DEMATEL) method has been developed. The use of DEMATEL has led to a ranking model of those barriers and a map of how the barriers are connected to each other.

The findings reveal that “I4.0 training”, “Lack of Motivation” and “Resistance to Change” are the most significant barriers for adopting Industry 4.0 in RMG sector of Bangladesh based on their prominence scores.

These findings will help the people who make decisions in the RMG industry of Bangladesh, such as company owners, managers and the executive body, come up with a plan for putting I4.0 practices into place successfully. The decision-making framework developed in this research can be utilized by the RMG industry of Bangladesh and other similar industries in developing countries to figure out how important each barrier is for them and how to get rid of them in order of importance.

As far as the authors are aware, there has not been a comprehensive study of the barriers inhibiting the adoption of I4.0 within the scope of Bangladeshi RMG industry. This work is the first to uncover these barriers and analyze them using the combination of Delphi technique and DEMATEL.

The purpose is to understand how the role of quality functions might evolve amidst digitalisation and an increased focus on services. This study focuses on customer feedback and how it can function as activation triggers for developing absorptive capacity, as well as how it relates to the value creation processes.

Following a qualitative research design, the authors gathered primary data from interviews with quality managers at 17 UK and Swedish firms and triangulated it with secondary information from the firms' web pages.

The findings show that customer feedback-based activation triggers can support development of absorptive capacity in the quality function if there are established processes for acting on customer feedback. This is often the case for codified feedback, which normally concerns products. However, digitalisation offers new opportunities of engaging in value co-creation, and firms need to develop digital capabilities to manage new technologies and data analytic tools. For personalised feedback (the main category of service-related feedback), established processes are missing.

This study work contributes to knowledge about how quality functions respond to customer feedback on both products and services. It clarifies why the quality function sometimes struggles to contribute to service quality as much as to product quality. From a theory development perspective, the authors contribute to understanding customer feedback-based activation triggers, how they lead to development of absorptive capacity and their relation to value co-creation on a functional level.

The purpose of this paper is to show a comparative study of different direction-of-arrival (DOA) estimation techniques, namely, multiple signal classification (MUSIC) algorithm, delay-and-sum (DAS) beamforming, support vector regression (SVR), multivariate linear regression (MLR) and multivariate curvilinear regression (MCR).

The relative delay between the microphone signals is the key attribute for the implementation of any of these techniques. The machine-learning models SVR, MLR and MCR have been trained using correlation coefficient as the feature set. However, MUSIC uses noise subspace of the covariance-matrix of the signals recorded with the microphone, whereas DAS uses the constructive and destructive interference of the microphone signals.

Variations in root mean square angular error (RMSAE) values are plotted using different DOA estimation techniques at different signal-to-noise-ratio (SNR) values as 10, 14, 18, 22 and 26dB. The RMSAE curve for DAS seems to be smooth as compared to PR1, PR2 and RR but it shows a relatively higher RMSAE at higher SNR. As compared to (DAS, PR1, PR2 and RR), SVR has the lowest RMSAE such that the graph is more suppressed towards the bottom.

DAS has a smooth curve but has higher RMSAE at higher SNR values. All the techniques show a higher RMSAE at the end-fire, i.e. angles near 90°, but comparatively, MUSIC has the lowest RMSAE near the end-fire, supporting the claim that MUSIC outperforms all other algorithms considered.

Family business in the Czech Republic has a very short history, which creates inequalities in the conditions of family business compared to other countries. The aim is to find out whether, despite the disadvantages resulting from historical development, the approach of Czech family business owners to digitization differs from that of business owners existing in an environment with a long history of family business.

The respondents of the online questionnaire survey conducted in spring 2024 are family business owners from the Czech Republic. About 500 valid responses were obtained, mainly from small manufacturing businesses. The hypotheses were statistically verified. To analyse the relationships between variables, coefficients were used (Pearson’s, Spearman’s, Gamma, Kendall’s or Kruskal–Wallis test). Factor analysis was used to identify hidden variables that may explain the relationships between the observed variables.

Key findings related to the approaches of generations owned and managed to the implementation of digitization, the influence of non-family managers and owners, the main barriers to implementation or the expected benefits. The finding that, despite the large historical distance, the attitudes of historically young family businesses do not differ much from those of owners in countries with a long history of family businesses can be considered novelties. It demonstrates that family businesses are mainly influenced by their specific characteristics brought about by the intermingling of family and business, regardless of the history of the development of the business environment.

This research highlights a key insight into family business dynamics: the cultural and historical context appears to have a less significant impact on owners’ attitudes than the inherent characteristics shared across family businesses. In essence, the unique blend of family and business interests creates commonalities that transcend geographical or historical differences. Comparing family business owners from the former “Eastern Bloc” and those from countries that have not been hampered by this social scrutiny provides a new perspective in the discipline of family business. Groups of barriers to the introduction of digitization were identified, namely resources, changes, data security and employees.

Incumbent retail organisations need to develop new capabilities to adapt with the increasingly competitive retail landscape. Despite the growing relevance of innovation in retail practice, the strategic management of innovation in retailing is still vastly under-researched. This explorative study thus aims to investigate how incumbent retail firms can organise for innovation from an organisational ambidexterity perspective.

A single-case study of an established Swedish retail firm was conducted from December 2016 to July 2018 and followed up in June 2021. The authors followed the process of implementation of organisational changes aimed to increase innovation in the company, particularly the introduction of a digital marketing initiative and a corporate innovation hub. Data collection was based on nine semi-structured interviews and participant observations and unstructured interviews from 13 meetings and workshops. An abductive approach to data analysis was followed, iteratively comparing theoretical concepts and empirical data using open, axial and selective coding to distil findings into aggregated themes.

Given the inherently limited formalisation of innovation processes in most retail organisations, structural ambidexterity appears to be necessary when the aim is radical, strategic retail innovation. Structural mechanisms are able to safeguard the space and resources to focus on long-term research and projects with higher risk and uncertainty; however, integration of innovation activities to the mainstream organisation is critical. Pursuing contextual ambidexterity, wherein instead of structural solutions, employees are empowered to divide employees' time between innovation-related and efficiency-related tasks, is more likely related to retail innovations that are incremental and operational.

The paper contributes to the emerging topic of strategic management of innovation in retailing, by explicating how incumbent retailers can organise for innovation depending on the type of innovation that is aimed for, using organisational ambidexterity as a novel perspective.

The literature on leadership is quite extensive; however, this study explains the impact of leadership styles on career success, career competence and career adaptability in the health sector. It explains the impact of servant leadership on career competence and career adaptability with a serial mediating impact of psychological safety and proactive behavior as well as self-efficacy and proactive behavior.

It is a quantitative study, and it tested the suggested model in hospitals in Pakistan. The data were collected from 310 health practitioners from the hospitals, and it was analyzed with partial least square structural equation modeling.

The findings suggest that psychological safety and proactive behavior serially mediate the impact of servant leaders on career competence and career adaptability; hence, servant leadership tends to increase career competence and career adaptability of individuals. One more serial mediation has been tested with positive results between servant leadership and career competence and career adaptability.

The study takes a very well theoretically linked model which tests the serial mediating path of servant leadership to career competencies and career adaptability.

Despite increasing focus among scholars and practitioners on the design of product-service systems (PSS), there exists no compilation of current knowledge on the role played by small and medium-sized enterprises (SMEs) in designing such systems. Thus, this paper sets out to identify and organise the existing research and suggest questions for future research.

A systematic literature review was performed to identify and provide in-depth details on key themes in the literature addressing the design of PSS in SMEs.

This paper identifies five themes in the literature on the design of PSS in SMEs: motives, challenges, SME characteristics, methods and digitalisation. The themes are interrelated, and SME characteristics seem to be at the core as they are related to all the other themes. Gaps in the current knowledge are identified, and questions for future research are suggested.

The suggestions for future research provide a starting point for expanding the research on PSS design and devising practical support for SMEs.

There is still an ongoing debate on the value relevance of capital structure and its determinants. Recently the issue has been explored in family firms after being explored in mature firms. This paper investigates the role of institutional investors and the firm's innovation activity in influencing the firm's decision and ability to acquire debt capital.

A large sample of 700 privately-held family firms in Italy from 2010 to 2019. Two analysis techniques are used: panel analysis and path analysis. The value of debt and the debt ratio are used as leverage measures. The value of patent (as a proxy for innovation) and institutional investor are the explanatory variables.

The results show that institutional investors have no relationship with financial leverage measures except when controlling for an interaction variable (Institutional investors × Lombardy region). The patent value is positively correlated with debt; however, the ratio patent-to-asset is negatively related to financial leverage indicating higher risk exposure. The nonlinearity test demonstrates a turning point when the relationship between patent value and debt inverts.

Firms should monitor their innovation activity since excessive innovation increases risk exposure and affects financing opportunities and value. The involvement of institutional investors does not always enhance value.

Existing literature focuses separately on family firm innovations and financial leverage as outcome variables, emphasizing the role of institutional investors in both fields by adopting agency theory and socioemotional wealth framework. In this study, the authors go further by merging both relationships, investigating the dynamics of the institutional-family firm innovation relationship in influencing the firm's capital structure. The authors contribute to the ongoing debate by providing original findings on capital structure, governance and innovation, supported by rigorous methods to enhance family firms' decision-making.