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Financial institutions have a role in harmonising economic purposes with environmental and social purposes through transmission mechanisms whereby the institutions provide channels to promote socially and environmental desirable activities. This study explores the sustainability criteria disclosed at firm-level corporate social responsibility reports for the purpose of providing direction for financial institutions committed to enhancing the contribution to sustainability objectives.

The Delphi Method and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) system have been employed to systematically analyse the opinions of 15 experts regarding the operation of the 7 Taiwanese financial institutions listed on the Dow Jones Sustainability Index in 2019 with respect to the capacity to affect sustainability objectives.

The findings reveal a high prominence level for corporate governance, law compliance, risk management and occupational safety and health, representing amongst the sustainability criteria considered. This suggests that financial institutions may benefit from focussing resources on these areas, starting with corporate governance, when considering means for enhancing the sustainability performance.

The study is limited by the small number of financial institutions available in Taiwan which suggests that further research could be directed towards a larger sample of financial institutions, say by international comparison, expanding the range of industries studied or the inclusion for additional sustainability indicators.

Overall, the study has shed light on Taiwan's financial institutions' capacity to contribute to sustainable practices which is an area that has not been extensively investigated. This study may have useful implications for financial institutions in Taiwan.

The authors also recognise other factors that are likely to contribute to social impacts. These include human capacity building and development, information security, green procurement, green building and climate-related financial products.

This study fills the gap by providing useful insights for a better understanding of sustainable development in financial institutions by promoting sustainability practice in general. The authors' analysis will assist decision-makers in identifying and prioritising the driving factors and thus adopting suitable strategies to strengthen sustainability performance.

As a counterproductive interpersonal work behavior, knowledge hiding inhibits team creativity, hampers collaboration and ultimately has a detrimental impact on organizational performance. Drawing upon the impression management perspective. This study aims to investigate how and when employees’ political skill affects their knowledge-hiding behavior in real work contexts.

The authors tested the hypotheses using data gathered from 266 employees in China using a time-lagged research design.

The results indicate that political skill positively influences knowledge hiding through the supplication strategy. Moreover, the positive effect of political skill on this strategy is stronger under higher levels of competition.

A cross-sectional design and the use of self-report questionnaires are the limitations of this study.

The authors contribute to the literature on the emergence of knowledge hiding by identifying an impression management perspective. The authors also contribute to the literature on political skill by exploring the potential negative effects of political skill in the interpersonal interaction. Moreover, the authors enrich the understanding of the literature in competitive climate by introducing the impression management theory and exploring its influence on knowledge floating.

The demand for the cold chain logistics of agricultural products was investigated through demand forecasting; targeted suggestions and countermeasures are provided. This paper aims to discuss the aforementioned statement.

A Markov-optimised mean GM (1, 1) model is proposed to forecast the demand for the cold chain logistics of agricultural products. The mean GM (1, 1) model was used to forecast the demand trend, and the Markov chain model was used for optimisation. Considering Guangxi province as an example, the feasibility and effectiveness of the proposed method were verified, and relevant suggestions are made.

Compared with other models, the Markov-optimised mean GM (1, 1) model can more effectively forecast the demand for the cold chain logistics of agricultural products, is closer to the actual value and has better accuracy and minor error. It shows that the demand forecast can provide specific suggestions and theoretical support for the development of cold chain logistics.

This study evaluated the development trend of the cold chain logistics of agricultural products based on the research horizon of demand forecasting for cold chain logistics. A Markov-optimised mean GM (1, 1) model is proposed to overcome the problem of poor prediction for series with considerable fluctuation in the modelling process, and improve the prediction accuracy. It finds a breakthrough to promote the development of cold chain logistics through empirical analysis, and give relevant suggestions based on the obtained results.

This research aims to investigate the influence of building design on the thermal comfort of occupants of naturally ventilated hospital (NVH) wards to identify the aspects with the most significant influence on the thermal comfort of hospital buildings during the hot-dry season in the hot-humid tropics of Southeast Nigeria.

Field measurements, physical observations and a questionnaire survey of 60 occupants of the wards of the Joint Presbyterian Hospital, Uburu in Ebonyi State, Nigeria were undertaken. The data were analysed using Humphreys' neutral temperature formula, descriptive statistics and multiple regression analysis.

The results revealed that the neutral temperature for the wards ranges from 26.2 °C to 29.9 °C, the thermal condition in the wards was not comfortable because it failed to meet the ASHRAE Standard 55 as only 65% of the occupants said the thermal condition was acceptable. The number and sizes of windows, building orientation, the presence of high-level windows and higher headroom significantly influenced the occupants' thermal comfort vote.

This research is valuable in estimating comfort temperature and identifying aspects that require attention in enhancing the capacity of NVH wards to effectively meet the thermal comfort needs of occupants in the hot-humid tropics of Southeast Nigeria and other regions that share similar climatic conditions.

To the best of the authors’ knowledge, this is the first study of this nature that provides valuable feedback for building design professionals on the performance of existing hospital buildings in meeting users' thermal comfort needs in the hot-dry season of the hot-humid tropics in Southeast Nigeria.

Firms may suffer differently from the patent thickets in a particular technology field. This paper explores how patent thickets affect the financial performance of firms with different patent propensities and technological leadership.

From the perspective of patent strategy, the authors study how patent propensity, the possibility that a firm applies for patents, affects the patent thickets and financial performance. Additionally, this paper uses patent stock to measure technological leadership, the degree to which a firm can develop, maintain and enhance technology and product innovation, to study the impact of patent propensity on firms. A three-way interaction model is used to explore the relationship among patent thickets, patent propensity, technological leadership and financial performance based on an unbalanced panel of 69 Chinese telecommunication equipment firms from 2008 to 2019.

The authors find that patent propensity positively moderates patent thickets and financial performance. Notably, technological leadership negatively moderates the moderating effect of patent propensity.

This paper enriches the heterogeneous literature of patent thickets and financial performance. It sheds light on the fact that firms with different technological leadership may use different patent strategies to cut through patent thickets.

This study aims to investigate the rising trend of virtual influencers – digitally created characters with human-like attributes. It aims to evaluate and compare their effectiveness with human influencers in terms of brand attitudes and purchase intentions. It uncovers the mechanisms underlying the differences in effectiveness observed between virtual influencers and their human counterparts.

The research uses a 2 (influencer type: human vs virtual) × 3 (product type: functional vs symbolic vs experiential) between-subjects design. Through a pilot study (n = 334) and a main study (n = 352), the research examines the interactive effects of influencer and product type on brand attitude and purchase intentions. Hypotheses were developed and tested using moderating mediation models centered on authenticity and product–endorser fit.

Virtual influencers are perceived as less authentic than human influencers across all product types, negatively influencing brand attitude and purchase intention. However, the extent to which influencer type affects brand attitudes and purchase intentions, mediated by product–endorser fit, varies based on the product type.

This research emphasizes two key mechanisms – authenticity and product–endorser fit – influencing the effectiveness of virtual influencers. It suggests that aligning virtual influencers with suitable product types can offset their perceived authenticity deficit, significantly affecting their endorsement effectiveness.

From a technological determinist perspective, machine learning (ML) may significantly contribute towards sustainable development. The purpose of this study is to synthesize prior literature on the role of ML in promoting sustainability and to encourage future inquiries.

This study conducts a systematic review of 110 papers that demonstrate the utilization of ML in the context of sustainable development.

ML techniques may play a vital role in enabling sustainable development by leveraging data to uncover patterns and facilitate the prediction of various variables, thereby aiding in decision-making processes. Through the synthesis of findings from prior research, it is evident that ML may help in achieving many of the United Nations’ sustainable development goals.

This study represents one of the initial investigations that conducted a comprehensive examination of the literature concerning ML’s contribution to sustainability. The analysis revealed that the research domain is still in its early stages, indicating a need for further exploration.

This study provides a configurational examination of how policy designs influence the innovation performance of the emergency industry in China.

This study employs the Data Envelopment Analysis Malmquist index (DEA-Malmquist) to quantify the innovation performance of the emergency industry and then codes the innovation policies to calculate the syntactic components based on institutional grammar tools (IGTs). The configurations of syntactic components were determined by applying the fuzzy-set qualitative comparative analysis (fsQCA).

The results indicate that rules- and norms-oriented policy designs would improve the innovation performance of China's emergency industry. In the developed provinces, the “Deontic” and “aIm” combinations in the policy are useful for improving performance. In the developing provinces, the ambiguity of the “aIm” and “Context” conditions in the policy is leading to low performance. Additionally, a lack of strategy-oriented policy design would also result in poor performance.

Most previous studies used substitute variables to understand policy impacts. This study contributes to identifying the impacts of the syntactic components of policy designs on the innovation performance of the emergency industry. The findings can assist policymakers in developing more effective policies to stimulate innovation development in the emergency industry.

Perishable inventory management for the grocery sector has become more challenging with extended omnichannel activities and emerging consumer expectations. This paper aims to identify and formalize key performance measures of omnichannel perishable inventory management (OCPI) and explore the influence of operational and market-related factors on these measures.

The inductive approach of this research synthesizes three performance measures (product waste, lost sales and freshness) and four influencing factors (channel effect, demand variability, product perishability and shelf life visibility) for OCPI, through industry investigation, expert interviews and a systematic literature review. Treating OCPI as a complex adaptive system and considering its transaction costs, this paper formalizes the OCPI performance measures and their influencing factors in two statements and four propositions, which are then tested through numerical analysis with simulation.

Product waste, lost sales and freshness are identified as distinctive OCPI performance measures, which are influenced by product perishability, shelf life visibility, demand variability and channel effects. The OCPI sensitivity to those influencing factors is diverse, whereas those factors are found to moderate each other's effects.

To manage perishables more effectively, with less waste and lost sales for the business and fresher products for the consumer, omnichannel firms need to consider store and online channel requirements and strive to reduce demand variability, extend product shelf life and facilitate item-level shelf life visibility. While flexible logistics capacity and dynamic pricing can mitigate demand variability, the product shelf life extension needs modifications in product design, production, or storage conditions. OCPI executives can also increase the product shelf life visibility through advanced stock monitoring/tracking technologies (e.g. smart tags or more comprehensive barcodes), particularly for the online channel which demands fresher products.

This paper provides a novel theoretical view on perishables in omnichannel systems. It specifies the OCPI performance, beyond typical inventory policies for cost minimization, while discussing its sensitivity to operations and market factors.

The purpose of the research is to analyze the factors that determine the intention of small- and medium-sized enterprises (SMEs) to adopt the Metaverse. For this purpose, the analysis of the effort expectancy and performance expectancy of the constructs in relation to business satisfaction is proposed.

The analysis was performed on a sample of 182 Spanish SMEs in the technology sector, using a PLS-SEM approach for development. For the confirmation of the model and its results, an analysis with PLSpredict was performed, obtaining a high predictive capacity of the model.

After the analysis of the model proposed in this research, it is recorded that the valuation of the effort to be made and the possible performance expected by the companies does not directly determine the intention to use immersive technology in their strategic behavior. Instead, the results obtained indicate that business satisfaction will involve obtaining information, reducing uncertainty and analyzing the competition necessary for approaching this new virtual environment.

The study represents one of the first approaches to the intention of business behavior in the development of performance strategies within Metaverse systems. So far, the literature has approached immersive systems from perspectives close to consumer behavior, but the study of strategic business behavior has been left aside due to the high degree of experimentalism of this field of study and its scientific approach. The present study aims to contribute to the knowledge of the factors involved in the intention to use the Metaverse by SMEs interested in this field.