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Amid challenges posed by the COVID-19 pandemic, fostering employee creativity has become paramount for organizations. However, there is a scarcity of research on digitalization of the workplace and its implications for implementing high involvement work systems (HIWSs) in organizations, particularly in relation to their impact on employee outcomes, such as creativity and job satisfaction. Additionally, limited attention has been given to the role of job level and organizational type in driving change during times of adversity. This study aims to examine the factors within the HIWSs model using the PIRK model – power (P), information sharing (I), rewards (R) and knowledge (K) to explore how HIWSs shape the extent of power individuals have over their employment, the sharing of information, the types of rewards that engage and motivate employees and the knowledge required to fulfil employees’ responsibilities effectively, both individually and collectively.

Using a qualitative research methodology, this study uses thematic analysis for data collection, analysis and interpretation. Semi-structured interviews (n = 48) served as the primary data collection method. Using the theoretical lenses of high-involvement practices and employee perceptions of PIRK, the effect on employee creativity and job satisfaction is analysed.

The findings of this study reveal that employee creativity is significantly influenced by how employees perceive power, information, rewards and knowledge. Moreover, the study highlights the role of transformational and transactional leadership in shaping employee perceptions of power, information and knowledge within HIWSs. A high perception of PIRK is found to positively impact employee job satisfaction.

This study offers valuable insights for human resource management (HRM) professionals seeking to make informed decisions regarding best practices and initiatives for enhancing employee outcomes in the post-COVID era. By recognizing the pivotal role of HIWSs and their influence on employee perceptions, organizations can strategically implement HIWSs to foster creativity and job satisfaction. Furthermore, this research contributes to the existing literature by examining the interplay between HIWSs and the PIRK model in the context of workplace digitalization, emphasizing the importance of adapting HRM practices to address the evolving needs of the modern workforce.

This study will help HRM professionals in making informed decisions on the best practices and initiatives to enhance employee outcomes in the post-COVID era. This paper adds to the existing literature on HIWS and PIRK in the context of workplace digitalization.

This paper aims to explore the student psychological contract in the post-pandemic induced hybrid mode of the academic ecosystem in residential business schools of India. The study puts forth three facets of understanding student expectations for contract fulfillment: the business school, academic staff (faculty) and peers.

Using a sequential mixed methodology (qualitative and quantitative), data were gathered and analyzed in two phases. Perceptions of students regarding their expectations were captured through in-depth semi-structured telephonic interviews. The sample comprised 64 students pursuing two years of full-time master's in management courses at four residential business schools in India. Data obtained through interviews were analyzed using thematic analysis. The themes extracted were prioritized using the analytical hierarchy process (AHP) in the second phase.

The study provides insight into the prioritized expectations of students from their peers, academic staff and the institute. The findings of the study propose that though the expectations may differ across different groups, the mutual interdependence of these groups was mandatory for contract fulfillment.

Research on student psychological contracts in the hybrid mode of business education is scarce. The study provides a holistic perspective on this from the lens of students.

This paper aims to explore the relationship between owner-manager or leader’s ambidextrous leadership style and its effect on human resource management (HRM) practices, contextual ambidexterity and knowledge-intensive small- and medium-enterprises (SMEs) strategic agility.

This study presents an in-depth qualitative case study analysis of two knowledge-intensive SMEs from India’s information technology and health-care products industry serving a range of global clients. Using the theoretical lenses of empowerment-focused HRM practices, ambidextrous leaders, contextual ambidexterity and strategic agility, semi-structured interview data of leaders, managers and employees of the case organizations were analysed. Through a two-staged analytical process, we abductively developed a novel conceptual framework at the intersection of the above theoretical lenses.

The findings suggest that the knowledge-intensive SME’s strategic agility, ambidexterity and empowerment-focussed HRM approach was influenced by the owner-manager or leader’s ambidextrous leadership style and their philosophy towards managing people and had a positive impact in creating a culture of trust, participation, risk-taking and openness, and led to delivering innovative products and services as well as several positive employee-level outcomes.

Recent literature reviews on HRM In SMEs highlight several gaps, including the impact of owner-manager or leader’s philosophy of managing people in shaping HRM practices and employee outcomes. This paper thus adds to the existing literature on HRM and knowledge-intensive SMEs.

The purpose of this paper is to explore use of community treatment orders (CTOs) in adults with intellectual disability (ID) and mental health problems across England and Wales.

A web-based exploratory survey was sent to 359 consultants on the database of the Faculty of the Psychiatry of ID, Royal College of Psychiatrists who had declared ID as their main speciality. Socio-demographic details of responding consultants, clinical characteristics of adults with ID on CTO, subjective views of consultants on using CTOs in people with ID were collected and analysed.

In total, 94 consultant questionnaires were returned providing information on 115 patients detained under CTO. More than 75 per cent of the respondents had used CTO in their clinical practice. Patients subject to CTO were generally young, white males with mild ID and living in supported accommodation. CTOs were primarily used in situations of non-engagement (52.2 per cent), non-compliance with medication (47 per cent) or non-compliance with social care supports (49.6 per cent).

Responding consultants expressed concerns about encroachment of civil liberties and ethics of using CTOs in people with ID who may lack capacity and stressed that decision to use CTOs needs to be therefore done on individual basis.

This is the first national study to examine the practice of applying CTOs in adults with ID and mental disorders. Current practice is based on evidence from research done in adults with normal intelligence. Further research is needed to investigate the utility of CTOs in routine clinical practice in adults with ID and mental disorders.

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?

The purpose of this paper is to investigate how employer brand experience (EBE) impacts organizational citizenship behavior (OCB). In addition, it aims to identify the mediating role of employee engagement (EE) in relationship between EBE and OCB.

To test the research hypotheses, a web questionnaire was developed and data were collected from 426 respondents working in the Indian banking sector. Hypotheses were tested using structural equational modeling.

EBE was positively related to OCB. The predicted mediating role of EE in the relationship between EBE and OCB was also supported.

The study is confined to the banking sector only, which limits the generalization of the findings.

The results imply that firms should leverage on various dimensions of employer brand (EB) i.e. compensation, work–life balance, working environment, training and corporate social responsibility to enhance EE and OCB.

The research is among the very few to confirm the role of EBE vis-à-vis current employees especially in a collectivist society like India. The study also confirmed the mediating role of EE between EBE and OCB which have not been studied previously.

Using consumption value theory, this study aims to examine the impact of tourists’ perceived consumption value dimensions of tea beverages offered by Hong Kong (HK)-style cafés, including taste value, price value, health value and emotional value, on tourists’ memorable experience (ME), satisfaction and revisit intention.

Using an online survey, this study collected 225 usable data from tourists who had experience in visiting HK-style cafés. Partial least squares–structural equation modelling was used to examine the importance of tourists’ value dimensions, including taste value, price value, health value and emotional value, on tourists’ ME, satisfaction and revisit intention.

The results revealed that taste value, price value, health value and emotional value are significant predictors of tourists’ ME in HK-style cafés, which in turn drive their satisfaction and revisit intention.

This study focusses on a single context: HK-style cafés. Future research may enhance the generalisability of the findings by replicating the model in other countries with diverse cultures.

Tourism marketers may strengthen tourists’ ME, satisfaction and revisit intention by promoting tea beverages as well as HK-style cafés. Tourism marketers are recommended to communicate taste value, price value, health value and emotional value of HK-style tea beverages, which in turn encourages tourists to learn about the features of tea beverages. Subsequently, it drives tourists’ ME and satisfaction, thereby strengthening their intention to revisit.

This study contributes to the tourism marketing literature by providing an understanding of the role of tea beverage value in driving tourists’ ME, satisfaction and revisit intention. By empirically testing a research model, this study confirms that specific consumption value elements of tea beverages, namely, taste value, price value, health value and emotional value, are critical drivers in driving tourists’ ME, satisfaction and revisit intention.

The purpose of this study is to provide a novel portfolio asset prediction by means of the modified deep learning and hybrid meta-heuristic concept. In the past few years, portfolio optimization has appeared as a demanding and fascinating multi-objective problem, in the area of computational finance. Yet, it is accepting the growing attention of fund management companies, researchers and individual investors. The primary issues in portfolio selection are the choice of a subset of assets and its related optimal weights of every chosen asset. The composition of every asset is chosen in a manner such that the total profit or return of the portfolio is improved thereby reducing the risk at the same time.

This paper provides a novel portfolio asset prediction using the modified deep learning concept. For implementing this framework, a set of data involving the portfolio details of different companies for certain duration is selected. The proposed model involves two main phases. One is to predict the future state or profit of every company, and the other is to select the company which is giving maximum profit in the future. In the first phase, a deep learning model called recurrent neural network (RNN) is used for predicting the future condition of the entire companies taken in the data set and thus creates the data library. Once the forecasting of the data is done, the selection of companies for the portfolio is done using a hybrid optimization algorithm by integrating Jaya algorithm (JA) and spotted hyena optimization (SHO) termed as Jaya-based spotted hyena optimization (J-SHO). This optimization model tries to get the optimal solution including which company has to be selected, and optimized RNN helps to predict the future return while using those companies. The main objective model of the J-SHO-based RNN is to maximize the prediction accuracy and J-SHO-based portfolio asset selection is to maximize the profit. Extensive experiments on the benchmark datasets from real-world stock markets with diverse assets in various time periods shows that the developed model outperforms other state-of-the-art strategies proving its efficiency in portfolio optimization.

From the analysis, the profit analysis of proposed J-SHO for predicting after 7 days in next month was 46.15% better than particle swarm optimization (PSO), 18.75% better than grey wolf optimization (GWO), 35.71% better than whale optimization algorithm (WOA), 5.56% superior to JA and 35.71% superior to SHO. Therefore, it can be certified that the proposed J-SHO was effective in providing intelligent portfolio asset selection and prediction when compared with the conventional methods.

This paper presents a technique for providing a novel portfolio asset prediction using J-SHO algorithm. This is the first work uses J-SHO-based optimization for providing a novel portfolio asset prediction using the modified deep learning concept.

This study aims to propose a theoretical model to explain mobile payment (MP) continuance usage in a physical store in Indonesia from a habit perspective. In detail, continuance usage was argued to be a consequence of habitual behavior which is related to specific actions conducted automatically, repeatedly and frequently. Therefore, the theoretical model was constructed on the theory of habit establishment.

In total, 220 Indonesian respondents were used to examine the theoretical model. Furthermore, a cross-sectional study was used through the use of a descriptive statistical approach to preparing data and descriptive analyses and structural equation modeling method for analysis.

Satisfaction was found to have the most substantial direct influence on the establishment of habit to use MP followed by perceived usefulness and perceived compatibility. Meanwhile, deal proneness and social ties were discovered to have a significant indirect effect on habit through the mediation of usefulness.

This study used the theory of habit formation to understand how user develops repeated behavior in MP usage which leads to continuance usage of the platform. There is limited explicit exploration and development of a theory based on this concept, therefore, this study is a contribution to the body of knowledge with respect to habit formation and its impacts on MP continuance usage.

This study aimed to investigate the mediating roles of social and personal norms in the relationships between transcendent values (i.e. altruistic and biospheric) and responsible computer acquisition behaviour (RCAB). Previous studies suggested the role of norms in explaining the value–behaviour relationship. However, they did not provide sufficient evidence of the mediating roles of both personal and social norms.

A self-administered questionnaire was employed to gather data from 571 consumers in Malaysia. The data were analysed using the structural equation modelling method.

It was found that personal and social norms partially mediate the relationship between altruistic values and RCAB. Social norms also partially mediate the relationship between altruistic values and personal norms. However, there was no significant relationship between biospheric values and RCAB; thus, the norms have no mediation roles.

It provides policymakers and marketers insights into ways of encouraging pro-environmental behaviour such as RCAB.

This research provides empirical evidence of the mediating roles of personal and social norms in value–behaviour relationships in an emerging market context.