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The purpose of this paper is to empirically examine the impact of supply chain risks (SCRs) and demand management strategies (DMSs) on the company performance in order to study the use of DMSs in delivering improved results even in the presence of SCRs. The SCRs considered under the study are as follows: demand variability, constrained capacity and quality of services delivery, and competitive performance, customer satisfaction and financial performance are the measures considered for company performance.

This study is based on a survey of 439 businesses in India representing 10 groups of services industries (information technology/IT enabled services, business process outsourcing, IT infrastructure, logistics/transportation, healthcare, hospitality, personal services, consulting, education and training, consumer products and retail), using structural equation modeling (SEM) methods.

The findings reveal that presence of demand variability risk has significant influence upon the use of demand planning and forecasting, controlling customer arrival during peaks and shifting demand to future. Mismatch of capacity against demand (unused capacity) leads to the use of techniques to influence business during lean periods, thereby resulting in enhanced supply chain (SC) and financial performance. Controlling customer arrival during peaks to shift the demand to lean periods leads to enhanced financial performance. Presence of delivery quality risk does not significantly influence the use of DMS. Also, short-term use of customer and business handling techniques does not exert significant influence on company performance.

The study has limitations as follows: (1) respondents are primarily from India while representing global organizations, (2) process/service redesign to relieve capacity as a DMS is not considered and (3) discussion on capacity management strategies (CMSs) is also excluded.

SC managers can be resourceful in shifting the peak demand to future with the application of techniques to control customer arrival during peaks. The managers can also help enhance business by influencing business through offers, incentives and promotions during lean periods to use available capacity and improve company performance.

This study is one of the first empirical works to explore how presence of SCRs influences the use of DMS and impacts the three types of company performance. The study expands current research on demand management options (DMOs) by linking three dimensions of company performance based on the data collected from ten different groups of service industry.

The purpose of this paper is to discuss the relationships between person–job fit and job satisfaction, the mediating role of career self-management and the moderating role of job demands.

In this paper, 947 employees were surveyed using questionnaires, and hypothesis testing was conducted using structural equation modeling in Mplus.

Person–job fit was found to be positively related to career self-management, and career self-management plays a mediating role in the positive relationship between person–job fit and job satisfaction. Statistical analysis also confirmed that job demands moderate both the relationship between person–job fit and career self-management, as well as the relationship between person–job fit and job satisfaction via career self-management.

The results of a single study offer limited generalizability and should thus be applied with caution. More cross-industry and cross-company studies should be conducted to verify the applicability of the findings to other industries, cultures and geographical contexts.

Managers should try to enhance employees' person–job fit and help or encourage them to engage in career self-management to increase job satisfaction. Additionally, managers should be aware of the negative influence of job demands and try to keep them at low levels.

This study extends and enriches the understanding of the positive influence of person–job fit on work outcomes, explores the mechanism of person–job fit on job satisfaction from a new perspective, namely career self-management, and explores the boundary condition (i.e. job demands) of the relationship between person–job fit and career self-management in the Chinese context.

Digitalization, innovation and changing customer requirements drive the continuous improvement of an organization's business processes. IT demand management (ITDM) as a methodology supports the holistic governance of IT and the corresponding business process change (BPC), by allocating resources to meet a company's requirements and strategic objectives. As ITDM decision-makers are not fully aware of how the as-is business processes operate and interact, making informed decisions that positively impact the to-be process is a key challenge.

In this paper, the authors address this challenge by developing a novel approach that integrates process mining and ITDM. To this end, the authors conduct an action research study where the researchers participated in the design, creation and evaluation of the approach. The proposed approach is illustrated using two sample demands of an insurance claims process. These demands are used to construct the artefact in multiple research circles and to validate the approach in practice. The authors applied learning and reflection methods for incrementally adjusting this study’s approach.

The study shows that the utilization of process mining activities during process changes on an operational level contributes to (1) increasing accuracy and efficiency of ITDM; (2) timely identification of potential risks and dependencies and (3) support of testing and acceptance of IT demands.

The implementation of this study’s approach improved ITDM practice. It appropriately addressed the information needs of decision-makers and unveiled the effects and consequences of process changes. Furthermore, providing a clearer picture of the process dependencies clarified the responsibilities and the interfaces at the intra- and inter-process level.

This research aims to answer two major research questions related to the COVID-19 crisis from a longitudinal approach: What is the revenue management (RM) role during the different periods subject to analysis? What are the RM strategies and measures implemented during this crisis in contrast with a non-crisis context? It also aims to propose an RM implementation model that provides a contingency plan to face future crises.

This qualitative study, following a longitudinal approach, analyses three round-table discussions with 11 internationally renowned experts during three key scenarios of the COVID-19 crisis: the lockdown period (from March to June 2020) and the following two summer seasons (the post-lockdown period): Post-lockdown I (the summer campaign, 2020) and Post-lockdown II (the summer campaign, 2021). Based on a deductive approach, thematic analysis is conducted using NVivo.

Further professionalisation of revenue managers, which has enabled the correct application of strategies and measures, highlighting the importance of not lowering prices, the flexibility of booking conditions, the development of other sources of income and the increase in the value of services, amongst others, are key factors in managing this crisis. The longitudinal analysis carried out in three different periods of this crisis shows how these measures have evolved and the contrast with RM application in a non-crisis context. The revenue manager's leadership and proactivity, the holistic organisation of RM marketing, commercial and sales departments and the quick adaptation of RM systems (RMSs) by modifying their algorithms are essential to reducing the impact of COVID-19 on the hospitality industry. This crisis has led the industry to rethink processes and strategies and to increase digitalisation. The proposed model, which considers the various RM strategies and measures implemented during COVID-19 in contrast to a non-crisis context, is the cornerstone for developing a graded contingency plan to face future crises. This research sheds light on the widely discussed role of RM during this crisis.

This study has various limitations. First, the three round-table discussions were held online due to the health crisis, and the chosen webinar format may have biased the participants' answers due to its public nature. Second, the survey was carried out in Spanish. Despite the strong international profiles of the participants, cultural distortion may appear, suggesting that the research should possibly be extended to other cultural contexts in the future. Third, some of the participants were unable to attend all the round-table discussions due to their professional duties, so people with similar profiles were invited to the rest of the sessions.

The revenue manager's leadership and proactivity, the holistic organisation of RM marketing, commercial and sales departments and the quick adaptation of RMSs by modifying their algorithms are essential to reducing the impact of COVID-19 on the hospitality industry. This crisis has led the industry to rethink processes and strategies and to increase digitalisation. The proposed model, which considers the various RM strategies and measures implemented during COVID-19 in contrast to a non-crisis context, is the cornerstone for developing a graded contingency plan to face future crises. This research sheds light on the widely discussed role of RM during this crisis.

This work contributes to the literature by providing a model that considers the various RM strategies and measures implemented during COVID-19 in contrast to a non-crisis context. The novelty of this research is mainly found in the conducting of a deductive and longitudinal study considering previous research focussed on RM strategies applied during the COVID-19 crisis and supplementing it with new measures by applying qualitative techniques.

The need to address energy management as a significant innovation in the smart grid is emphasized to enable a more effective penetration of renewable energy to achieve energy savings and CO₂ emission reductions. The purpose of this study is to propose a holistic, flexible decision framework for energy management in a smart grid.

According to the situation actor process−learning action performance (SAP−LAP) model, the variables have been identified after a comprehensive analysis of the literature and consideration of the opinions of domain experts. However, the importance of each SAP−LAP variable is not the same in real practice. Hence, focus on these variables should be given based on their importance, and to measure this importance, an interpretive ranking process based ranking method is used in this study. This helps to allocate proportionate resource to each SAP−LAP variable to make a better decision for the energy management of the smart grid.

This study ranked five actors based on their priorities for energy management in a smart grid: top management, generator and retailor, consumers, government policy and regulation and technology vendors. Furthermore, actions are also prioritized with respect to performance.

The SAP−LAP model conveys information about the state of energy management in India to actors who may proceed or manage the flow of electricity. Additionally, this study aids in detecting vulnerabilities in the current energy generation, transmission and distribution technique. The synthesis of SAP results in LAP, which assists in recommending improvement actions learned from the current situation, actors and processes.

The SAP−LAP model is a revolutionary approach for examining the current state of energy management in a unified framework that can guide decision-making in conflicting situations, significantly the contradictory nature of India’s renewable energy and power sectors.

This study aims to examine the relationship between polychronicity, job autonomy, perceived workload, work–family conflict and high work demand on the health-care employee turnover intention during the COVID-19 pandemic.

The authors conducted quantitative research in private hospitals using a self-administered questionnaire, and 264 respondents participated. The authors also used an analysis of moment structures to determine the relationship between independent and moderating variables.

The results show a significant positive relationship between polychronicity, job autonomy, perceived workload, work–family conflict and high work demand, affecting turnover intention. This study also found the moderating effect of high work demand on work–family conflict and turnover intention.

This research was limited to hospitals in Bahrain during the COVID-19 pandemic. Nevertheless, the findings highlight the factors associated with health-care employee turnover intention and only five factors were identified.

This study enhances the theoretical and practical effects of turnover intention. The results provide a competitive benchmark for hospital managers, administrators and governing bodies of employee retention.

It advances economics and management theory by enhancing the understanding of health-care employees’ turnover intention in Bahrain. It serves as a basis for future large-scale studies to test or refine existing theories.

To the best of the authors’ knowledge, this study is the first to adopt extrinsic variables in self-determination theory to measure the turnover intention of health-care employees. However, using resources in a crisis can be applied to any disaster.

Audit hour reporting is rare internationally. Thus, to what extent shareholders have the power to influence audit effort/hour demand is a question left unanswered. This study aims to use unique South Korean data to determine whether the increasing power of the largest foreign/domestic shareholders and blockholders can influence audit hour demand.

In this study ordinary least squares (OLS) regression analysis is conducted using a sample of Korean listed firms over the 2004–2018 sample period.

The results show: as the percentage equity holding of the largest foreign shareholder and blockholder (>5%) increases, audit hour demand increases. As the shareholding of the largest domestic shareholder increases, audit hour demanded decreases. The association between audit fees/hours is not qualitatively indifferent, after controlling for the audit fee premium effect. Furthermore, the largest foreign shareholder is shown to demand increasingly higher levels of audit hours from Big4 auditors, relative to NonBig4. All results are consistent with audit demand theory.

Whilst previous studies offer audit fee/risk interpretations, this study extends the literature by developing a framework to explain why audit hour demands differ for specific groups. Because audit hour information is rare internationally, the study has important policy implications.

The purpose of this paper is to determine the inventory replenishment policies when demand rate is a function of the inventory space allocated to the products on retail shelves. Existing results on inventory policies with inventory-level-dependent demand (ILDD) assume deterministic functional forms of the demand rate. In this paper, the authors model the inventory decisions when demand is a function of shelf-space allocation and random uncertainty. The authors provide managerial insights of this paper's results.

The demand rate is assumed to be a function of shelf-space allocation based on two settings in the literature. First, the authors model the demand rate as a function of initial shelf-space allocation. In the next setting, the authors assume that the demand rate is a function of instantaneous inventory level on shelves. In both the settings, the authors also model random demand uncertainty in addition to the shelf-space dependency of demand rate. The objective is to maximize the expected profit and determine the inventory parameters.

In addition to the demand uncertainty, the authors consider linear, power and exponential functional forms of demand rate. Inventory policy that maximizes expected profit is determined when demand rate is a function of initial allocation and displayed inventory level. The results are implementable for practitioners for optimizing the shelf-space allocation and related inventory policy.

Most of the extant results on inventory policy with shelf-space-dependent demand do not model the demand uncertainty. The authors model a variety of functional forms of demand rate with ILDD in addition to the demand uncertainty. The results are a building block for more applications in inventory management for real-life applications.

Scientific description of the organization and management of a temporary large scale healthcare (T-LSHc) vaccination clinic and evidence-based guidance for future temporary healthcare (T-Hc) services.

Mixed-methods rapid feedback case study, using interviews, document analysis and quantitative data, with both data collection and analysis guided by a research-informed systems program theory of the clinic.

Private contractors were not willing to bid for contracts to set up and close a T-LSHc vaccination clinic in 2022, although they had done so earlier in the year. The public health system was able successfully to set up and run the clinic itself for 2 months, serving 3,000 people a day at its peak. Part of the success was because a dedicated unit to set up and run T-Hc services had been created in 2020. The Stockholm organization model differed from the Milan model by using information technology to reduce the need for a large number of on-site doctors.

There may be recall bias in interview data as interviews were carried out four months after the closing of the clinic. The conclusions apply to clinically simple but managerially complex T-Hc services but are limited to public healthcare systems operating in a similar context to that of the case study service. The study contributes to the new science of healthcare crisis organization and management and fills gaps in knowledge in disaster medicine for enduring and fluctuating health crises. The findings show the importance of a capacity to establish and manage T-Hc, and of the specialist management and HIT competence that health systems will need to build to meet the crises that threaten our health, both now and in the future.

Public healthcare systems can provide clinically simple and managerially complex T-Hc services quickly and successfully if they have experience and capacity to plan and set up such services, skilled operational managers respected by staff, staff who can be redeployed, and suitable health information technology.

The need for healthcare services to respond to crises is likely to increase in the future. Information for creating the service may be limited at first and changing. The exact nature of the health threat may be uncertain, as may the demand and needs of subpopulations and individuals. The study findings can help to respond quickly to reduce morbidity illness and death through creating and organizing temporary large-scale public healthcare services when existing services cannot be reorganized to meet the scale of the need.

This article is the first detailed empirical description and analysis of a large-scale temporary healthcare service operated by the primary care division of an integrated public healthcare system, with research informed guidance for future services of this type in similar contexts. This article compares two organization models of T-LSHc services, and contributes to an emerging subdiscipline of the organization and management of disaster and crisis healthcare.

Spare Parts Management (SPM) and Industry 4.0 has proven their importance. However, employment of Industry 4.0 solutions for SPM is at emerging stage. To address the issue, this article is aimed toward a systematic literature review on SPM in Industry 4.0 era and identification of research gaps in the field with prospects.

Research articles were reviewed and analyzed through a content-based analysis using four step process model. The proposed framework consists of five categories such as Inventory Management, Types of Spares, Circularity based on 6Rs, Performance Indicators and Strategic and Operational. Based on these categories, a total of 118 research articles published between 1998 and 2022 were reviewed.

The technological solutions of Industry 4.0 concepts have provided numerous opportunities for SPM. Industry 4.0 hi-tech solutions can enhance agility, operational efficiency, quality of product and service, customer satisfaction, sustainability and profitability.

The review of articles provides an integrated framework which recognizes implementation issues and challenges in the field. The proposed framework will support academia and practitioners toward implementation of technological solutions of Industry 4.0 in SPM. Implementation of Industry 4.0 in SPM may help in improving the triple bottom line aspect of sustainability which can make significant contribution to academia, practitioners and society.

The examination uncovered a scarcity of research in the intersection of SPM and Industry 4.0 concepts, suggesting a significant opportunity for additional investigative efforts.