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Taiwan’s hotel industry was adversely impacted by the COVID-19 pandemic. This study aims to examine the effect of strategic choices by Taiwanese international tourist hotels before and during the pandemic environments.

A data envelopment analysis (DEA)-based Malmquist methodology is used in this study to provide a mechanism to assess Taiwanese hotel strategy performance. Changes in the productivity and performance of Taiwanese international tourist hotels were analyzed in the periods before and during the pandemic to uncover insights useful should a similar crisis occur in the future. Panel data were obtained from the annual report of international tourist hotels published by the Taiwan Tourism Bureau from 2017–2020. Two groups of hotels were analyzed in this study: city hotels and scenic hotels.

The findings of this study reveal that chain hotels tended to perform better than independent hotels in both city and scenic areas during the global pandemic. Specifically, the crisis caused a substantial decline in productivity and profitability for international tourist hotels in Taipei City during the COVID-19 period. Compared to city hotels, findings also indicate that most international tourist hotels in scenic areas were able to maintain better productivity, including larger-sized scenic hotels.

The DEA-based analysis provides unique and valuable insights for hotel firm leaders on how to better identify and make strategic choices when responding to future crises.

The retail landscape is dramatically changing due to a series of socio-economic and technological challenges, which can be faced through the adoption of smart technologies. Accordingly, a significant number of publications in this field have been produced, albeit with fragmented results. Therefore, this paper aims at both providing a clear and organised overview of the main smart technologies for physical retailing, in terms of application fields and expected impact, while identifying the major shortcomings and future research avenues.

The research conducts a systematic review of the literature concerning the assimilation of smart technologies within physical retail environments, resulting in the analysis of 103 papers published from 2005 to 2023. The review highlights (1) the main smart technologies employed in retail stores, (2) their application area and (3) the beneficiaries of their adoption. Accordingly, these three aspects are initially assessed independently and then examined in combination.

The analysis presents a comprehensive list of 16 key technologies (what) that can support a wide range of processes, spanning from back-end functions to front-end activities, also enabling the connection with online channels (where), catering several and different benefits (why) to both customers and retailers (who). Besides, the research points out many uncovered topics that could be addressed by the academic community.

To the best of the authors’ knowledge, the review is the first one in the literature offering a thorough and organised overview of the different available technologies for in-store application and their impact on physical retail processes.

(1) This research aims to identify the relationship between authentic leadership (AL) and job engagement (JE) perceived by university teachers and (2) to investigate the relationship between AL and JE by the mediation of occupational self-efficacy (OSE).

This research is descriptive in nature, and thus, a quantitative research method is used to find the impact of AL on employee work engagement and the mediating role of employee trust and OSE. In this research, convenience sampling technique was used, a type of non-probability sampling method where the sample is taken from a group of people who are easily accessible. The sample chosen for this research comprised of 95 employees working at different universities in Bangladesh. Primary and secondary data collection methods are being used in this research. The data are collected from primary sources through questionnaires with close-ended questions.

The findings of this study support the previous studies Hassan and Ahmed (2011) indicate that the authentic behavior of leaders promotes healthy work environment that fosters the trust level of employees. When leaders are authentic, genuine and honest toward their employees and maintain transparency in an organization, it influences and motivates employees' work engagement. Furthermore, the results are supported by Hsieh and Wang’s (2015) research, which found that the relational transparency behavior exhibited by authentic leaders influences employees' self-efficacy (SE). When a leader openly shares ideas, opinions and clearly states what is expected from them, it will increase employees’ OSE and makes them more willing to get themselves engaged.

The limitations of this study were the shortage of time constraints, due to which a quantitative method was adopted to gather the data. The sample size was comprised of 95 respondents and does not represent the entire population of Bangladesh. To analyze the data, we have used the convenience sampling technique, which does not cover every sector of Bangladesh. Moreover, employees were reluctant to provide accurate data. This study is based on the perspective of university teachers only and does not explore AL from supervisors’ perspectives. Further research is required to explore this relationship from the perspective of both supervisor and employee. The sample size should be increased to cover the other regions of Bangladesh in order to represent the population. Cultural variables may also be included for future research purposes to examine the relationship between AL and work engagement because the culture of an organization determines the leadership style of a leader.

Despite the recent attention from government universities to develop the performance of public sector teaching staff, scientific public management research is developing unfortunately restricted (Osborne, 2016). Moreover, the findings of this study depict the importance to understand the constructions like leaders' authenticity that lead to the promotion of confidence in their employees and, as such, an increase in their JE and performance. In managerial implication, this study has provided useful information to the management of the private and public sectors. With this information, the management will be able to know how to increase the engagement and commitment of employees. This research will help academic professionals in public and private sector universities to know how AL style positively influences employees’ engagement.

This is an original work with practical value.

The aim of this study is to investigate subject independent emotion recognition capabilities of EEG and peripheral physiological signals namely: electroocoulogram (EOG), electromyography (EMG), electrodermal activity (EDA), temperature, plethysmograph and respiration. The experiments are conducted on both modalities independently and in combination. This study arranges the physiological signals in order based on the prediction accuracy obtained on test data using time and frequency domain features.

DEAP dataset is used in this experiment. Time and frequency domain features of EEG and physiological signals are extracted, followed by correlation-based feature selection. Classifiers namely – Naïve Bayes, logistic regression, linear discriminant analysis, quadratic discriminant analysis, logit boost and stacking are trained on the selected features. Based on the performance of the classifiers on the test set, the best modality for each dimension of emotion is identified.

 The experimental results with EEG as one modality and all physiological signals as another modality indicate that EEG signals are better at arousal prediction compared to physiological signals by 7.18%, while physiological signals are better at valence prediction compared to EEG signals by 3.51%. The valence prediction accuracy of EOG is superior to zygomaticus electromyography (zEMG) and EDA by 1.75% at the cost of higher number of electrodes. This paper concludes that valence can be measured from the eyes (EOG) while arousal can be measured from the changes in blood volume (plethysmograph). The sorted order of physiological signals based on arousal prediction accuracy is plethysmograph, EOG (hEOG + vEOG), vEOG, hEOG, zEMG, tEMG, temperature, EMG (tEMG + zEMG), respiration, EDA, while based on valence prediction accuracy the sorted order is EOG (hEOG + vEOG), EDA, zEMG, hEOG, respiration, tEMG, vEOG, EMG (tEMG + zEMG), temperature and plethysmograph.

Many of the emotion recognition studies in literature are subject dependent and the limited subject independent emotion recognition studies in the literature report an average of leave one subject out (LOSO) validation result as accuracy. The work reported in this paper sets the baseline for subject independent emotion recognition using DEAP dataset by clearly specifying the subjects used in training and test set. In addition, this work specifies the cut-off score used to classify the scale as low or high in arousal and valence dimensions. Generally, statistical features are used for emotion recognition using physiological signals as a modality, whereas in this work, time and frequency domain features of physiological signals and EEG are used. This paper concludes that valence can be identified from EOG while arousal can be predicted from plethysmograph.

This paper aims to provide a new method to study and improve the dynamic characteristics of the four-column resistance strain force sensor through the elastomer structure design and optimization.

Based on the mechanism analysis method, the authors first present a dynamic characteristic model of the four-column resistance strain force sensors’ elastomer. Then, the authors verified and modified the model according to the Solidworks finite element simulation results. Finally, the authors designed and optimized two types of four-column elastomers based on the dynamic characteristic model and verified the improvement of sensor dynamic performance through a hammer knock dynamic experiment.

The Solidworks finite element simulation and hammer knock dynamic experiment results show that the relative error of the model is less than 10%, which confirms the accuracy of the model. The dynamic performance of the sensors based on the model can be improved by more than 30%, which is a great improvement in sensor dynamic performance.

The authors first present a dynamic characteristic model of the four-column elastomer and optimize the four-column sensors successfully based on the mechanism analysis method. And a new method to study and improve the dynamic characteristics of the resistance is provided.

The purpose of this paper is to explore and further the existing knowledge on supply chain integration (SCI). This study proposes a model and several hypotheses to better understand some SCI antecedents, dependence and resource commitment and their relationships with performance.

Based on diverse theoretical approaches, the author develops and tests an integrated model in which dependence and resource commitment are proposed to enhance external integration, leading to an increase in economic performance. This study's empirical validity is reinforced by collecting data from 142 manufacturing firms in Spain and Germany and testing the model using structural equation model (SEM).

The results support dependence and resource commitment as antecedents of SCI, both with a positive effect. Also, discrepancies in the effect of external integration on performance are found where supplier integration seems not to have any effect on performance.

This study helps to better understand SCI antecedents. It makes both theoretical and managerial contributions by empirically analyzing both antecedents. This furthers extant knowledge regarding the joined impact of resource commitment and dependence on SCI. In particular, it incorporates resource commitment by considering it as the sacrifice firms need to implement to get involved in a long-term relationship.

Social exchange theory predicts that perceptions of employee/employer exchange relationships may change as employees add educational qualifications. Literature also suggests that more innovative individuals, who are particularly important to organisations, may be more likely to change jobs. The purpose of this study is to test how the innovativeness of an individual differs in its contribution to retention when subjected to different mediating and moderating influences indicated in the literature, for a cohort of employees that are undertaking degree studies while working.

To test theory that suggests certain implications for employee turnover, the part-time studies unit of a large South African university offering degree studies by evening classes was sampled, yielding 323 useable responses, with a response rate of about 30%. Structural equation modelling (SEM) is used to test a theoretical model predicting certain mediating and moderating influences on the relationship between individual innovativeness and turnover intentions.

Individuals with higher innovativeness self-report higher turnover intentions, which seem to be reduced by the mediating effects of perceived supervisor support and job satisfaction. Perceptions of distributive justice and core self-evaluations, which may be associated with an individual's evaluation of the social exchange relationship, are found to directly enable retention.

A model of moderation and mediation relationships between employee innovativeness and turnover intentions is derived from the literature and tested, offering novel insights into how to retain valuable staff in this context.

This study aims to comparatively analyze the systematic, idiosyncratic and downside risk exposure of both Islamic and conventional funds in Pakistan to see which of the funds has higher risk exposure.

The study analyzes different types of risks involved in both Islamic and conventional funds for the period from 2009 to 2016 by using different risk measures. For systematic and idiosyncratic risk single factor CAPM and multifactor models such as Fama French three factors model and Carhart four factors model are used. For downside risk analysis different measures such as downside beta, relative beta, value at risk and expected short fall are used.

The study finds that Islamic funds have lower risk exposure (including total, systematic, idiosyncratic and downside risk) compared with their conventional counterparts in most of the sample years, and hence, making them appear more attractive for investment especially for Sharīʿah-compliant investors preferring low risk preferences.

As this study shows, Islamic mutual funds exhibit lower risk exposure than their conventional counterparts so investors with lower risk preferences can invest in these kinds of funds. In this way, this research provides the input to the individual investors (especially Sharīʿah-compliant investors who want to avoid interest based investment) to help them with their investment decisions as they can make a more diversified portfolio by considering Islamic funds as a mean for reducing the risk exposure.

To the best of the author’s knowledge, this study is the first attempt at world level in looking at the comparative risk analysis of various types of the risks as follows: systematic, idiosyncratic and downside risk, for both Islamic and conventional funds, and thus, provides significant contribution in the literature of mutual funds.