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Introduction: Cost competitiveness, customer focus, and sustainability compliance are essential for new-age firms to survive and succeed in the VUCA market environment. This study examines how automobile corporations have improved cost competitiveness, productivity, and product quality.

Purpose: This study examines the importance of cost competitiveness, customer focus, and sustainability compliance for the long-term survival of organisations in VUCA markets, looking at the practical efforts made by automobile corporations to enhance cost competitiveness, productivity, and quality.

Methodology: The study utilises a comprehensive analysis of the strategies and initiatives implemented by the selected automobile companies. It involves a review of relevant literature, case studies, financial data analysis, and interviews with key industry experts, providing a holistic understanding of the actions taken by these organisations to achieve their goals.

Findings: The study reveals that cost competitiveness, customer focus, and sustainability compliance are critical factors for the long-term survival and success of organisations in the automotive industry. The analysed automobile companies have undertaken practical efforts to improve cost competitiveness, enhance productivity, and ensure high-quality products, enabling them to navigate the challenges and maintain a competitive edge.

Significance: The findings of this study contribute to a deeper understanding of the importance of cost competitiveness, customer focus, and sustainability compliance in the automotive industry. It highlights the need for organisations to constantly monitor both qualitative and quantitative profit to avoid complacency and ensure long-term efficiency. The study’s insights are relevant to businesses operating in other sectors, as they face similar challenges in the VUCA market environment.

This study proposes a methodology based on data source triangulation to measure the “strategic fit” for the automotive supply chain.

At first, the authors measured the responsiveness of the Indian automobile supply chain, encompassing the top ten major automobile manufacturers, using both sentiment and conjoint analysis. Second, the authors used data envelopment analysis to identify the frontiers of their supply chain. The authors also measured the supply chain's efficiency, using the balance sheet. Further, the authors analyzed the “strategic fit” zone and discussed the results.

The results indicate that both the proposed methods yield similar outcomes in terms of strategic fitment.

The study outcomes facilitate measuring the strategic fit, thereby leveraging the resources available to align. The methodology proposed is both easy to use and practice. The methodology eases time and costs by eliminating hiring agencies to appraise the strategic fit. This valuable method to measure strategic fit can be considered feedback for strategic actions. This methodology could also be incorporated possibly as an operative measurement and control tool.

Data triangulation meaningfully enhances the accuracy and reliability of the analyses of strategic fit. Data triangulation leads to actionable insights relevant to top managers and strategic positioning of top managers within a supply chain.

The paper aims to provide an understanding of how the transfer of progressive human resource management (HRM) practices may or may fail to render multinational enterprises (MNEs) institutional entrepreneurs creating change in job quality and decent work to underprivileged workers in the low-pay retail sector in Japan.

The paper draws on survey questionnaire data and interviews with workers and management in a foreign retailer in Japan.

The findings suggest that even where MNEs may provide some measurable material improvements in job quality, in this case equal pay for equal work, the total outcomes are nevertheless shaped by institutional context and constraints. In this case, the improvement in pay was intertwined with flexibility demands that were possible to meet for some workers but not others. In particular, women with care responsibilities and competing demands on their time were not able to experience “decent work” in the same way as others.

The study had a relatively low response rate, due to lack of discretion over time experienced by workers in Japan, as well as limited data on program outcomes, with interviews conducted with a small number of participants.

The study suggests that spaces and opportunities exist for MNEs to diverge from dominant practices in given host country locations and exercise a level of agency as emissaries of decent work but successful outcomes require a very thorough understanding of individual worker experiences within the institutional constraints of given environments.

The study offers insights into the complexities of initiatives by MNEs to contribute to the provision of decent work, particularly for workers in underprivileged positions including women in low-pay sectors such as retail, as firm-level practices lead to variable outcomes when filtered through local institutions.

The study brings together a focus on firm-level practices that inform much of the international HRM and international management scholarship with an emphasis on the experiences of workers, which is pursued in the sociology of work, to investigate whether MNEs can be actors in the realising of the Sustainable Development Goals around decent work.

This study aims to develop a machine learning model to detect structure fire fatalities using a dataset comprising 11,341 cases from 2011 to 2019.

Exploratory data analysis (EDA) was conducted prior to modelling, in which ten machine learning models were experimented with.

The main fatal structure fire risk factors were fires originating from bedrooms, living areas and the cooking/dining areas. The highest fatality rate (20.69%) was reported for fires ignited due to bedding (23.43%), despite a low fire incident rate (3.50%). Using 21 structure fire features, Random Forest (RF) yielded the best detection performance with 86% accuracy, followed by Decision Tree (DT) with bagging (accuracy = 84.7%).

Limitations of the study are pertaining to data quality and grouping of categories in the data pre-processing stage, which could affect the performance of the models.

The study is the first of its kind to manipulate risk factors to detect fatal structure classification, particularly focussing on structure fire fatalities. Most of the previous studies examined the importance of fire risk factors and their relationship to the fire risk level.

The present study investigates human behavioral and emotional experiences based on human-built environment interaction with a specific interest in urban graffiti displaying fear and pleasure-inducing facial expressions. Regarding human behavioral and emotional experience, two questions are asked for the outcome of human responses and two hypotheses are formulated. H1 is based on the behavioral experience and posits that the urban graffiti displaying fear and pleasure-inducing facial expressions elicit specified behavioral fear and pleasure responses. H2 is based on emotional experience and states that the urban graffiti displaying fear and pleasure-inducing facial expressions elicit specified emotional fear and pleasure responses.

The research design is developed as a multi-method approach, applying a lab-based experimental strategy (N:39). The research equipment includes a mobile electroencephalogram (EEG) and a Virtual Reality (VR) headset. The behavioral and emotional human responses concerning the representational features of urban graffiti are assessed objectively by measuring physiological variables, EEG signals and subjectively by behavioral variables, systematic behavioral observation and self-report variables, Self-assessment Manikin (SAM) questionnaire. Additionally, correlational analyses between behavioral and emotional results are performed.

The findings of behavioral and emotional evaluations and correlational results show that specialized fear and pleasure response patterns occur due to the affective characteristics of the urban graffiti's representational features, supporting our hypotheses. As a result, the characteristics of behavioral fear and pleasure response and emotional fear and pleasure response are identified.

The present paper contributes to the literature on human-built environment interactions by using physiological, behavioral and self-report measurements as indicators of human behavioral and emotional experiences. Additionally, the literature on urban graffiti is expanded by studying the representational features of urban graffiti as a parameter of investigating human experience in the built environment.

In recent decades, childhood in Japan has undergone significant transformations. Government policies geared at boosting women's labor force participation, a declining fertility rate, rising costs of having children on the one hand, and increased spending on public childcare and support measures for families, on the other hand, contribute to these ongoing changes. Having only one child is becoming the norm while mothers' role in society is shifting. The traditional family structure is moving from the previously predominant male breadwinner model to more dual-earner families. Children now spend significant amounts of time in care and education institutions.

In this chapter, we analyze current configurations of early childhood in institutions and the family from a policy perspective and regarding children's predominant education and care arrangements. Drawing on various survey data sets and evidence from demographic statistics to pedagogical ethnographies, we look at how childcare policies and families reshape the organization of children's lives and outline how institutions and educators create learning experiences aligned with the values of a collectivist society. However, despite being deeply rooted in traditional child-rearing goals, many parents also subscribe to rigorous educational arrangements from early childhood onwards to prepare children for success in a competitive education system. The chapter finishes with an outlook on future directions of how policymakers and the ongoing institutionalization of childhood continue to change children's lives.

Realistic composite vehicles with 2, 3, 5 and 9 axles, consisting of a truck with one or two trailers, are addressed in this paper by computational models for vehicle–bridge interaction analysis.

The vehicle–bridge interaction (VBI) models are formed by sets of 2-D rigid blocks interconnected by mass, damping and stiffness elements to simulate their suspension system. The passage of the vehicles is performed at different speeds. Several rolling surface profiles are admitted, considering the maintenance grade of the pavement. The spectral density functions are generated from an experimental database to form the longitudinal surface irregularity profiles. A computational code written in Phyton based on the finite element method was developed considering the Euler–Bernoulli beam model.

Several models of composite heavy vehicles are presented as manufactured and currently travel on major roads. Dynamic amplification factors are presented for each type of composite vehicle.

The VBI models for compound heavy vehicles are 2-D.

This work contributes to improving the safety and lifetime of the bridges, as well as the stability and comfort of the vehicles when passing over a bridge.

The structural response of the bridge is affected by the type and size of the compound vehicles, their speed and the conservative grade of the pavement. Moreover, one axle produces vibrations that can be superposed by the vibrations of the other axles. This effect can generate not usual dynamic responses.

This study aims to understand the dynamics underpinning the exit and re-entry strategies adopted by multinational enterprises (MNEs) in an emerging market, Pakistan.

This study undertook an in-depth historical case study of Yamaha Motorcycles, which had initially entered Pakistan as a joint venture but had then exited and re-entered as a wholly owned subsidiary.

This study found that, despite its status as a market leader and one of the older players in the Pakistani market, changing market dynamics in the 2000s – especially the increased competition brought by more affordable (inexpensive) Chinese motorcycles and the weak enforcement of industrial policies – had pushed Yamaha Motorcycles to exit. Another factor that had contributed to its exit were differences in risk perception and strategies with its local joint venture partner (a Pakistani business group). Hence, both firm-level and institutional factors had played significant roles in Yamaha’s market exit. This study further found that re-entering in a wholly owned subsidiary operation mode had been beneficial for the firm, as it gained a significant market share due to its focus on innovation and on capturing a market niche, which had earlier not been its main focus. The findings also suggest that opportunity logics and multiple forms of learning can be important for a firm’s re-entry into a host market – such as experiential (i.e. learning from experience) and vicarious learning (i.e. learning from other organizations, including suppliers and competitors) in an emerging market context, in which institutions evolve amid political and policy uncertainty. Finally, this study found that exit and re-entry timing is an important factor for the development of competitive advantage in a host market.

This study is among the few to have investigated the exit and re-entry strategies of MNEs in emerging markets. The relatively short time during which Yamaha Motorcycles had been out of the market had benefited it on its re-entry, as the firm had been able to capitalize on its prior learning and ties to suppliers’ networks.

A flexible manufacturing system (FMS) helps improve the system’s performance, thus increasing its overall competitiveness. FMS is an essential component of Industry 4.0 (I4.0), which has revolutionized the way firms manufacture their products. This study aims to investigate the diverse focus of the research being published over the years and the direction of scholarly work in applying FMSs in business and management.

A total of 1,096 bibliometric data were extracted from the Scopus database from the years 2001 to 2021. A systematic review and bibliometric analysis were performed on the data and related articles for performance measurement and scientific mapping on the FMS themes.

Based on co-keyword, the study reveals four major themes in the FMS field: mathematical models and quantitative techniques, scheduling and optimization techniques, cellular manufacturing and decision-making in FMSs. Based on bibliometric coupling on 2018–2021 bibliometric data, four themes emerged for future research: scheduling problems in FMS, manufacturing cell formation problem, interplay of FMS with other latest technologies and I4.0 and FMS.

The originality lies in answering the following research questions: What are the most highlighting themes in FMS, and how have they evolved over the past 20 years (2001–2021)? What topics have been at the forefront of research in FMS in the past five years (2016–2021)? What are the promising avenues of research in FMS?