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This study is based on the stimulus–organism–response (SOR) model to examine how job demands and technology overload affect work stress for workers using video conferencing apps (VCAs) in organizations during the COVID-19 pandemic. Moreover, the moderating effect of technology self-efficacy was tested in the model on the relationship between technology overload and work stress.

An online survey was conducted to investigate workers on PTT forums in Taiwan. A sample was obtained of 253 workers, and structural equation modeling was conducted using AMOS to test the hypotheses.

Job demands positively affect work stress through information overload, communication overload and system feature overload. Moreover, high technology self-efficacy may weaken the relationship between technology overload and work stress.

The study may have sample bias because our sample was obtained from an online survey on social networking sites. Regarding the theoretical implications, this study demonstrated that technology overload, as an internal organism, is a critical mediator influencing the relationship between job demands (stimulus) and work stress (response). Thus, this study extended the applicability of the SOR model in the context of working with VCAs in organizations.

Company managers need to effectively control the information amount, communication interruptions and system features of social media at optimum levels for workers. Moreover, companies should recruit workers with high technology self-efficacy or provide technology training and technology-related consulting to those with low technology self-efficacy.

The extant work stress knowledge is extended to workers using VCAs in organizations.

This study aims to discover a practical and effective way to apply the quality cost concept in Strategic Cost Management (SCM) framework. The interaction of preventive, appraisal and failure (PAF) activities in a company's internal value chain will be the starting point of SCM implementation.

This study begins by establishing value chain and quality costs as the scope of conceptual analysis. Discussions on the interrelationships between activities, quality and costs were gathered to clarify conceptual and practical gaps in the scope of the study. The PAF quality cost model is applied to find viable, practical solutions. The costs of activities will serve as performance indicators.

The PAF quality cost model depicts opportunities to lower costs and increase profit in a business simultaneously; current poor quality costs are the benchmark. Identifying PAF activities and costs in the business value chain and linking it with others is crucial in evaluating SCM applications. These linkages will generate a Quality Cost Chain (QCC). The leading indicator of improvement is a higher ratio between new possible failure costs (FC) and the combination of prevention and appraisal costs (PAC) than the current value, followed by a lower total quality cost (TQC). The subsequent attention is a lower ratio between the appraisal cost (AC) and prevention cost (PC). Mathematically, for assessing the operability of new quality-related activities, ΔPAC_new < ΔFC_new, TQC_new < TQC_current, (FC/PC)_new>(FC/PC)_current and (AC/PC)_new<(AC/PC)_current are proposed as feasible conditional-quantitative improvement criteria.

This study only discusses the relationship between quality costs and activities related to quality management in the PAF quality cost model, not cost behavior. This limitation opens up opportunities for future research that intends to link QCC with cost behavior in the context of managerial accounting and Strategic Cost Management. The use of QCC in certain industrial areas is the next research opportunity. The variety of PAF activities this study addresses originates from a wide range of industrial sectors; QCC research by sector may produce unique industrial quality cost phenomena.

QCC will make it easier for managers to evaluate how strategically their departments or activities contribute to quality costs at the departmental or organizational level, as well as to effectively and efficiently improve quality cost performance.

The quality-related activity and quality cost issues are still rarely treated as subjects of research studies in the field of Strategic Cost Management. Even so, the discussion tends to be very broad, complex and difficult to apply. This study combines a simple diagrammatic and mathematical approach to simplify the discussion and, at the same time, manage the value of strategic quality management.

Drawing on organizational design theory and organizational learning theory, this paper aims to examine component technology (CT) and the interaction between CT and experiential learning (EL) effects on the degree of integration (DI) of cross-border technological acquisitions.

Using a sample of 267 firms consisting of 229 acquirer firms who started cross-border technological acquisitions from developed economies and 38 acquirer firms who initiated cross-border technological acquisitions from emerging economies over the period of 1993–2016, this study adopts a value chain framework to measure the acquirers’ acquisition integration degree for the investigation of the effects of CT and the interaction between CT and EL.

First, this paper finds CT in cross-border technological acquisitions exerting a positive influence on the acquirer firm’s likelihood of the DI implementation, in line with the organizational design theory. Second, in view of organizational learning theory, this study finds EL and the combined effect of CT and EL to have an inverse influence on the DI.

The results imply that the moderating role of EL significantly optimizes decision choices for an acquirer firm for integration implementation strategies in the form of DI, such as full integration (structural integration), partial integration and no integration (structural separation), which appears to be crucial for cross-border technological acquisitions.

This study contributed to international business strategies by shedding light on the importance of the DI for an acquirer firm that undertakes a cross-border technological acquisition with a CT target firm. This study explains why structural integration might be necessary in cross-border technological acquisitions regardless of the costs of disruption it imposes, as well as the contexts in which it becomes less important or unnecessary. The study disclosed that the increase in the likelihood of DI because of CT depends on the EL of the acquisition company in the host country environment and fluctuates with the prior acquisition knowledge and EL of the host country. Combining two cross-border technological acquisition’s literature streams, such as CT and EL, this study enlightens the importance of organizational learning theory and theory of organization design strategic direction making on acquisition integration implementation strategies.

The transcript is of one from a number of interviews with disaster risk reduction (DRR) “pioneers” carried out in 2022 as a part of the United Nations Office for Disaster Risk Reduction (UNDRR) project to record the history of the field. It aims to enable one of the “pioneers” to explain his role in the emergence of disaster studies and provide critical commentary on what he considers is wrong with current DRR approaches.

Terry Cannon was interviewed to explain the beginnings of his involvement in disasters research and to comment on his views on progress in the field of disaster risk reduction since his early work in the 1980s. The transcript and video were developed in the context of the UNDRR project on the history of DRR.

The interview provides an account of the origins of the book “At Risk” and why it was considered necessary. This is put into the context of how the field of DRR has emerged since the 1980s. It elicits opinions on what he considers the gaps in both his early work (especially in the book “At Risk” of which he was a co-author) and in the field of DRR recently.

It provides historical context on how early disaster research developed the alternative framework of “social construction” of disasters, in opposition to the idea that they are “natural”. It challenges some of the approaches that have emerged as DRR and has been institutionalised, including its increasing difficulty in supporting the ideas of social construction.

This study aims to explore the grain chain in Kosovo. This study also aims to analyse the role of actors involved in the supply, production, processing, marketing and distribution of the grain value chain.

The study uses qualitative methods. A total of 60 semi-structured interviews are conducted with actors involved in the entire grain value chain.

Findings reveal that the country depends on grain imports and lacks an organised grain market, which is often distorted by the present political situation. Stakeholders are partly integrated in the grain value chain, and they are not very efficient in production. The existence of an informal market influences the decision-making of actors involved in the grain chain. The grain value chain displays mixed governance types, and the relationships among actors are based on the trust mechanism.

The research draws the importance of agriculture’s public policies to sustain domestic grain production. Public–private partnerships should be created to restore the grain market. Trading policies should be revised because they play a crucial role in enhancing fair competition between domestic and foreign traders.

Firms are engaging in eco-innovation as a response to environmental concerns. Due to its complexity, firms are searching, absorbing and using externally acquired knowledge toward implementing eco-innovation. Thus, this study aims to examine how different external knowledge sources affect the eco-innovation of small and medium-sized enterprises (SMEs) in developing economies.

The study uses an Ordered Probit regression analysis for 318 developing economy SMEs to examine the impact of vertical flows (suppliers and customers) and horizontal flows (competitors and scientific organisations) on eco-innovations.

On the vertical dimension, the results show that external knowledge from suppliers is positively associated with eco-product and eco-process innovations. However, external knowledge from customers is positively associated with eco-product innovation, but not eco-process innovation. On the horizontal dimension, external knowledge from competitors contributes to eco-process innovation, but not to eco-product innovation. Finally, external knowledge from scientific organizations is positively related to eco-product and eco-process innovations.

First, the study contributes to the external knowledge literature by focusing on developing country SMEs. Second, the methodology used in this study constitutes a novelty as it provides a tool that categorizes firms according to the extent of emphasis they placed on both eco-product and eco-process innovations. Finally, it offers new evidence by revealing that the effects of external knowledge on eco-innovations are differentiated and not equally beneficial to firms.

This research paper aims to analyze the scientific and grey literature on Quality 4.0 and zero-defect manufacturing (ZDM) frameworks to develop an integrated quality 4.0 framework (IQ4.0F) for quality improvement (QI) based on Six Sigma and machine learning (ML) techniques towards ZDM. The IQ4.0F aims to contribute to the advancement of defect prediction approaches in diverse manufacturing processes. Furthermore, the work enables a comprehensive analysis of process variables influencing product quality with emphasis on the use of supervised and unsupervised ML techniques in Six Sigma’s DMAIC (Define, Measure, Analyze, Improve and Control) cycle stage of “Analyze.”

The research methodology employed a systematic literature review (SLR) based on PRISMA guidelines to develop the integrated framework, followed by a real industrial case study set in the automotive industry to fulfill the objectives of verifying and validating the proposed IQ4.0F with primary data.

This research work demonstrates the value of a “stepwise framework” to facilitate a shift from conventional quality management systems (QMSs) to QMSs 4.0. It uses the IDEF0 modeling methodology and Six Sigma’s DMAIC cycle to structure the steps to be followed to adopt the Quality 4.0 paradigm for QI. It also proves the worth of integrating Six Sigma and ML techniques into the “Analyze” stage of the DMAIC cycle for improving defect prediction in manufacturing processes and supporting problem-solving activities for quality managers.

This research paper introduces a first-of-its-kind Quality 4.0 framework – the IQ4.0F. Each step of the IQ4.0F was verified and validated in an original industrial case study set in the automotive industry. It is the first Quality 4.0 framework, according to the SLR conducted, to utilize the principal component analysis technique as a substitute for “Screening Design” in the Design of Experiments phase and K-means clustering technique for multivariable analysis, identifying process parameters that significantly impact product quality. The proposed IQ4.0F not only empowers decision-makers with the knowledge to launch a Quality 4.0 initiative but also provides quality managers with a systematic problem-solving methodology for quality improvement.

The purpose of the chapter was to examine the impact of customer care chatbots on customer satisfaction levels in the mobile telephony industry in Zimbabwe, with a special focus on the company Econet Wireless. This chapter shows the conceptual framework used. An online questionnaire was administered to a sample of 100 Econet Wireless subscribers who were selected using probability stratified random sampling from Zimbabwe’s 10 provinces. The research data were collected and analysed for correlation, and a multiple regression analysis was carried out to identify the relationship between customer satisfaction and the three customer service improvements brought in by the introduction of customer service chatbots. The study discovered that there is a positive relationship between customer satisfaction levels and each of the three customer service improvements brought in by customer service chatbots, namely customer service convenience, speed of response, and omnichannel strategies. This study thereby proves that the introduction of customer service chatbots in the mobile telephony industry in Zimbabwe can lead to an improvement in customer satisfaction levels. However, addressing service quality only as a determinant of customer satisfaction in isolation is not sufficient to fully improve customer satisfaction levels. Therefore, organisations that seek to improve their customer satisfaction should consider strategies that address all determinants of customer satisfaction, namely price, product quality, service quality, situational factors, and personal factors. This study contributes to the body of knowledge, particularly regarding the use of artificial intelligence (AI) for customer service in developing economies.

This study aims to investigate the impact of organizational external environmental factors on strategic management accounting (SMA) usage in an emerging economy.

The study collected data from 79 public limited companies listed with the Dhaka Stock Exchange (Bangladesh) through a questionnaire survey. Multiple regression analysis is employed to test the impact of external environmental variables such as perceived environmental uncertainty and intensity of competition on SMA usage.

The study finds a significant positive impact of environmental uncertainty (fluctuation in the external environmental factors) and intensity of competition (domination by few companies) on SMA usage. However, the direction and magnitude of this impact vary considerably for specific groups of SMA practices such as costing, competitor accounting, customer accounting and planning and performance measurement techniques.

This study shows the impact of several facets of environmental uncertainty (i.e. unpredictability, fluctuation, ambiguity, lack of information and uncertainty of the outcome of decision) and intensity of competition (i.e. stressfulness and domination) in the empirical-based SMA research.