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Toyota's internationally coordinated production system in Asia and its selection of supply bases in South America and South Africa highlights the significance of recognizing global network firms and the global hub-and-spoke logistics system that has been developed to meet their needs. This system underpins the expansion of container shipping, air freight and telecommunications. Recognition of Main Street, linking Europe, Asia and North America with cui-desacs in Africa, Australasia and Central and South America, provides a framework for examining the relative importance of the system's hubs and terminals across different modes and regions. This analysis provides the basis for identifying and ranking key regional logistics platforms in Northeast Asia and their attraction as headquarter sites for global network firms. Examining the logistical situation pertaining after the end of the Cold War in the early 1990s and a decade later is used to gauge progress towards regional economic integration in Northeast Asia.

The purpose of this study is to better understand technology adoption and working from home (WFH) behaviour of micro and small enterprises (MSE) with 4 to 49 employees during the first (2020) and second (2021) COVID-19 lockdowns in Switzerland.

This study uses two data sets gathered using computer-assisted telephone interviewing surveys conducted with 503 managing directors of Swiss MSEs after the first and 506 MDs after the second COVID-19 lockdown period.

The study revealed that during the COVID-19 pandemic, WFH arrangements are related to the adoption of technology by Swiss industry groups. Furthermore, industry characteristics and technology adoption strategies are also associated with the long-term prospect of WFH. The overall result confirms the predominant role of technology pioneers.

The study focuses on MSEs in Switzerland during a specific period. The data set includes mainly quantitative data. Future studies could investigate larger enterprises in international contexts, integrating employees’ viewpoints founded on long-term gathered qualitative data. The implications of this study include predictions about future WFH behaviour in Swiss MSEs.

To the best of the authors’ knowledge, this is the first study collecting data in Swiss MSEs after the two COVID-19 lockdowns in 2020 and 2021. As a result, this study offers a unique perspective on a specific business segment, which accounts for around 70% of global employment.

The purpose of this study is to develop a method to assess social performance. Traditionally, environment, social and governance (ESG) rating providers use subjectively weighted arithmetic averages to combine a set of social performance (SP) indicators into one single rating. To overcome this problem, this study investigates the preconditions for a new methodology for rating the SP component of the ESG by applying machine learning (ML) and artificial intelligence (AI) anchored to social controversies.

This study proposes the use of a data-driven rating methodology that derives the relative importance of SP features from their contribution to the prediction of social controversies. The authors use the proposed methodology to solve the weighting problem with overall ESG ratings and further investigate whether prediction is possible.

The authors find that ML models are able to predict controversies with high predictive performance and validity. The findings indicate that the weighting problem with the ESG ratings can be addressed with a data-driven approach. The decisive prerequisite, however, for the proposed rating methodology is that social controversies are predicted by a broad set of SP indicators. The results also suggest that predictively valid ratings can be developed with this ML-based AI method.

This study offers practical solutions to ESG rating problems that have implications for investors, ESG raters and socially responsible investments.

The proposed ML-based AI method can help to achieve better ESG ratings, which will in turn help to improve SP, which has implications for organizations and societies through sustainable development.

To the best of the authors’ knowledge, this research is one of the first studies that offers a unique method to address the ESG rating problem and improve sustainability by focusing on SP indicators.

Logistics and supply chain management has been elevated to a strategic level whereby firms can simultaneously achieve differentiation and low cost for sustained competitive advantage. Empirical studies have often concentrated on logistics management in developed Western countries, displaying a bias towards the USA. This study applies the competency approach to explore logistics in Taiwan. A survey of 1,200 manufacturing firms was undertaken in order to examine the relationships between logistics competency, logistics performance, and financial performance, using exploratory factor analysis and the structural equation modelling technique. Four logistics competencies, namely, integration and knowledge competency, customer focused logistics competency, measurement competency, and agility competency were identified. The research findings revealed that (1) logistics competency was significantly related to logistics performance but not significantly associated with financial performance, and (2) logistics performance was positively associated with financial performance. These findings also implied that logistics competency has an indirect effect on financial performance through logistics performance. This finding confirmed the “world-class” logistics competencies (i.e. positioning, integration, agility, and measurement) as identified by MSUGLRT (1995). In addition, it suggests that logistics competency in a huge geographic area such as America can have the same effect in a smaller geographic area such as Taiwan.

This is a general review study aiming to specify the key customer-based factors and technologies that influence the value co-creation (VCC) process through artificial intelligence (AI) and automation in the hospitality and tourism industry.

The study uses a theory-based general literature review approach to explore key customer-based factors and technologies influencing VCC in the tourism industry. By reviewing the relevant literature, the authors conclude a theoretical framework postulating the determinants of VCC in the AI-driven tourism industry.

This paper identifies customers' perceptions, attitudes, trust, social influence, hedonic motivations, anthropomorphism and prior experience as customer-based factors to VCC through the use of AI. Service robots, AI-enabled self-service kiosks, chatbots, metaversal tourism and new reality, machine learning (ML) and natural language processing (NLP) are technologies that influence VCC.

The results of this research inform a theoretical framework articulating the human and AI elements for future research set to expand the models predicting VCC in the tourism industry.

Few studies have examined consumer-related factors that influence their participation in the VCC process through automation and AI.

In the domain of healthcare, both process efficiency and the quality of care can be improved through the use of dedicated pervasive technologies. Among these applications are so-called real-time location systems (RTLS). Such systems are designed to determine and monitor the location of assets and people in real time through the use of wireless sensor networks. Numerous commercially available RTLS are used in hospital settings. The nursing home is a relatively unexplored context for the application of RTLS and offers opportunities and challenges for future applications. The paper aims to discuss these issues.

This paper sets out to provide an overview of general applications and technologies of RTLS. Thereafter, it describes the specific healthcare applications of RTLS, including asset tracking, patient tracking and personnel tracking. These overviews are followed by a forecast of the implementation of RTLS in nursing homes in terms of opportunities and challenges.

By comparing the nursing home to the hospital, the RTLS applications for the nursing home context that are most promising are asset tracking of expensive goods owned by the nursing home in order to facilitate workflow and maximise financial resources, and asset tracking of personal belongings that may get lost due to dementia.

This paper is the first to provide an overview of potential application of RTLS technologies for nursing homes. The paper described a number of potential problem areas that can be addressed by RTLS.

The objective of this research was to identify Facione’s six critical thinking skills using graduate students blogs as a reflection tool in the context of leadership using structured and unstructured blogs. The skills researched were (a) Interpretation, (b) Analysis, (c) Evaluation, (d) Inference,(e) Explanation, and (f) Self-Regulation (Facione, 1990). It was evident that providing students with guidelines for the purpose of blogging in the classroom was more thought evoking over the duration of the course compared to students following an open reflection. Self-Regulation and explanation were the skills used most consistently among participants. With this knowledge, how do educators encourage students to use the other four skills just as often?

The conducted examination of programming affordances and constraints had the purpose of adding knowledge and value that facilitate the on-going national curricula revision; knowledge that also could be of general interest outside the Swedish K-12 context.

With a qualitative approach, the study was conducted as a document analysis where submitted lesson plans were the base for a directed content analysis.

This study presents findings on how the involvement of programming in mathematics and technology have potential to foster engagement and motivation among students. Findings also indicate that the implementation of programming can develop important general skills that go beyond the boundaries of mathematics and technology. Moreover, the identified constraints could be valuable to improve the on-going curriculum development for K-12 mathematics and technology.

This qualitative study was conducted on a relatively small number of teachers where the majority has taken the courses on a voluntary basis. An important complement would be to conduct a larger quantitative study with data from a more general sample of K-12 teachers.

Results and discussions provide guidance for K-12 teachers and other stakeholders who want to introduce programming as a complementary tool in teaching and learning activities.

The study has a contribution to the on-going implementation of the Swedish national curricula for K-12 mathematics and technology.

During the last years, many studies have been published on teacher training in programming, and how the training can be improved. This study goes beyond the actual teacher training and examine aspects teachers translate to theirs daily work after completing the training.

The purpose of this study is to present and explain a new customer segmentation approach inspired by failure mode and effect analysis (FMEA) which can help classify customers into more accurate segments.

The present study offers a look at the three most commonly used approaches to assessing customer loyalty:net promoter score, loyalty ladder and loyalty matrix. A survey on the quality of restaurant services compares the results of categorizing customers according to these three most frequently used approaches.

A new way of categorizing customers through loyalty priority number (LPN) is proposed. LPN was designed as a major segmentation criterion consisting of customer loyalty rate, frequency of purchase of products or services and value of purchases. Using the proposed approach allows to categorize customers into four more comprehensive groups: random, bronze, silver and gold – according to their loyalty and value to the organization.

Survey will bring a more accurate way of categorizing customers even in those sectors where transaction data are not available. More accurate customer categorization will enable organizations to use targeting tools more effectively and improve product positioning.

The most commonly used categorization approaches such as net promoter score, loyalty ladder or loyalty matrix offer relatively general information about customer groups. The present study combines the benefits of these approaches with the principles of FMEA. The case study not only made it possible to offer a view of the real application of the proposed approach but also made it possible to make a uniform comparison of the accuracy of customer categorization.

This paper analyses the importance of leadership and culture in combating corruption in Hong Kong SAR, Japan, Malaysia, New Zealand, Singapore and Taiwan.

This paper is based on the comparative analysis of the effectiveness of the anti-corruption measures in the studies of six selected countries/regions in this special issue of Public Administration and Policy. The contributors in this special issue were invited because of their publications on combating corruption in the six countries/regions.

The critical variable ensuring the effectiveness of combating corruption is the strong political will of the leadership in changing the culture of corruption in the country/region by implementing a zero-tolerance policy toward corruption, as shown in Singapore and Hong Kong. In New Zealand’s case, leadership plays a less important role because of the population’s emphasis on equality and egalitarianism and its reliance on the Ombudsman and Serious Fraud Office to curb corruption. However, the corrupt leadership of Tanaka Kakuei in Japan, Najib Rajak in Malaysia, and Chen Shui-bian in Taiwan, demonstrates clearly their insidious impact of consolidating their kleptocratic rule in these countries/regions.

As the role of leadership and culture in combating corruption has not been given sufficient attention in the literature, this paper attempts to rectify this neglect by demonstrating that the political leaders in Singapore and Hong Kong, and to a lesser extent, New Zealand, have succeeded in minimising corruption while their counterparts in Japan, Taiwan and Malaysia, have failed to do so.