Search results

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.

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.

Digital labor platforms (DLPs) are transforming the nature of the work for an increasing number of workers, especially through extensively employing automated algorithms for performing managerial functions. In this novel working setting – characterized by algorithmic governance, and automatic matching, rewarding and punishing mechanisms – gig-workers play an essential role in providing on-demand services for final customers. Since gig-workers’ continued participation is crucial for sustainable service delivery in platform contexts, this study aims to identify and examine the antecedents of their working outcomes, including burnout and engagement.

We suggested a theoretical framework, grounded in the job demands-resources heuristic model to investigate how the interplay of job demands and resources, resulting from working in DLPs, explains gig-workers’ engagement and burnout. We further empirically tested the proposed model to understand how DLPs' working conditions, in particular their algorithmic management, impact gig-working outcomes.

Our findings indicate that job resources – algorithmic compensation, work autonomy and information sharing– have significant positive effects on gig-workers’ engagement. Furthermore, our results demonstrate that job insecurity, unsupportive algorithmic interaction (UAI) and algorithmic injustice significantly contribute to gig-workers’ burnout. Notably, we found that job resources substantially, but differently, moderate the relationship between job demands and gig-workers’ burnout.

This study contributes a theoretically accurate and empirically grounded understanding of two clusters of conditions – job demands and resources– as a result of algorithmic management practice in DLPs. We developed nuanced insights into how such conditions are evaluated by gig-workers and shape their engagement or burnout in DLP emerging work settings. We further uncovered that in gig-working context, resources do not similarly buffer against the negative effects of job demands.

This study aims to investigate the contribution of blockchain technology to supply chain risk management and its impact on performance among Indian manufacturing companies.

Drawing on a resource-based view, dynamic capability and system of systems theory, this study examines the direct relationships between blockchain, supply chain risk management and supply chain performance. The authors validate the mediating effects of three supply chain risk management components, namely supply risk management, demand risk management and cyber security management, on financial transaction reliability and information reliability. Data were collected from 204 Indian manufacturing companies that have adopted blockchain technology.

The results demonstrate that companies adopting blockchain technology have experienced positive outcomes in managing supply chain-related risks, financial transaction reliability and information reliability. These findings provide valuable guidance to managers, highlighting blockchain as a competitive advantage for supply chain management.

To the best of the authors’ knowledge, no previous research on blockchain-based risk management capabilities has been conducted.

The learning outcomes of this study are to identify and discuss ways in which energy consumption in a residential educational institute can be reduced by improving demand-side energy management for sustainable development; summarise the challenges that an institute faces in transitioning to a more environmentally friendly mode of operations concerning energy management; illustrate the difference between operating expense and capital expenditure methods used for solar rooftop projects from the perspective of Goa Institute of Management (GIM); and analyse different project proposals for solar rooftop power generation energy using capital budgeting techniques.

Dr Ajit Parulekar, director at GIM, was evaluating the steps taken over the past few years for sustainable energy management to understand their impact and consider ways in which to take the environmental sustainability agenda forward. One of the projects that he was considering was the rooftop solar power plant. GIM had received proposals from several different vendors and evaluated three proposals out of these. He needed to decide on the capacity of the rooftop solar power generation and the type of contract that he should get into for the implementation of the project. This case study describes the differences and highlights the advantages and disadvantages of all the mentioned models with respect to GIM.

This case study is suitable for post-graduate level management students, as well as for undergraduate-level finance and management students.

Teaching notes are available for educators only.

CSS4: Environmental management.

The relationship between employees, co-workers, and the company is crucial because it determines its success in achieving its goals. This engagement is strongly influenced by job demands and work resources at the company, affecting how employees feel about their workplace’s physical, psychological, and mental conditions. High job demands with supportive work resources can increase employee motivation and create an employee’s high commitment to the company. Digitalizing all human resources information systems will make it easier for employees to achieve their work targets, so digitalization has a role in strengthening or weakening the influence of work demands and resources on employee engagement. The concept is that existing job demands should be balanced with the availability of appropriate job resources to minimize or even eliminate psychological disturbances and improve employee health. This physically and psychologically healthy condition greatly supports the ability of employees to use digital technology in the human resources management (HRM) process.

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.

Conflict and violence are the main drivers of globally escalating humanitarian needs. Local grassroots initiatives are pivotal in distributing humanitarian supplies in the acute response phase until more established humanitarian aid organizations can enter. Nevertheless, scant research exists regarding the role of grassroots associations in providing humanitarian assistance during a military conflict. The purpose of this paper is to understand the role of grassroots associations and identify important themes for effective operations.

This paper adopts a case-study approach of three Ukrainian grassroots associations that began operating in the immediate days of the full-scale invasion of Ukraine. The findings are based on analyzing primary sources, including interviews with Ukrainian volunteers, and are supported by secondary sources.

Grassroots associations have local contacts and a contextual understanding of population needs and can respond more rapidly and effectively than large intergovernmental agencies. Four critical themes regarding the operations of grassroots associations emerged: information management, inventory management, coordination and performance measurement. Grassroots humanitarian response operations during conflict are challenged by personal security risks, the unpredictability of unsolicited supplies, emerging volunteer roles, dynamic transportation routes and shifting demands.

Grassroots responses are central to humanitarian responses during the acute phase of a military conflict. By examining the operations of grassroots associations in the early months of the 2022 war in Ukraine, the authors provide a unique perspective on humanitarian logistics. Nonetheless, more inclusive models of humanitarian responses are needed to harness the capacities and resilience of grassroots operations in practice.

This paper aims to minimize the mean-risk cost of sustainable and resilient supplier selection, order allocation and production scheduling (SS,OA&PS) problem under uncertainty of disruptions. The authors use conditional value at risk (CVaR) as a risk measure in optimizing the combined objective function of the total expected value and CVaR cost. A sustainable supply chain can create significant competitive advantages for companies through social justice, human rights and environmental progress. To control disruptions, the authors applied (proactive and reactive) resilient strategies. In this study, the authors combine resilience and social responsibility issues that lead to synergy in supply chain activities.

The present paper proposes a risk-averse two-stage mixed-integer stochastic programming model for sustainable and resilient SS,OA&PS problem under supply disruptions. In this decision-making process, determining the primary supplier portfolio according to the minimum sustainable-resilient score establishes the first-stage decisions. The recourse or second-stage decisions are: determining the amount of order allocation and scheduling of parts by each supplier, determining the reactive risk management strategies, determining the amount of order allocation and scheduling by each of reaction strategies and determining the number of products and scheduling of products on the planning time horizon. Uncertain parameters of this study are the start time of disruption, remaining capacity rate of suppliers and lead times associated with each reactive strategy.

In this paper, several numerical examples along with different sensitivity analyses (on risk parameters, minimum sustainable-resilience score of suppliers and shortage costs) were presented to evaluate the applicability of the proposed model. The results showed that the two-stage risk-averse stochastic mixed-integer programming model for designing the SS,OA&PS problem by considering economic and social aspects and resilience strategies is an effective and flexible tool and leads to optimal decisions with the least cost. In addition, the managerial insights obtained from this study are extracted and stated in Section 4.6.

This work proposes a risk-averse stochastic programming approach for a new multi-product sustainable and resilient SS,OA&PS problem. The planning horizon includes three periods before the disruption, during the disruption period and the recovery period. Other contributions of this work are: selecting the main supply portfolio based on the minimum score of sustainable-resilient criteria of suppliers, allocating and scheduling suppliers orders before and after disruptions, considering the balance constraint in receiving parts and using proactive and reactive risk management strategies simultaneously. Also, the scheduling of reactive strategies in different investment modes is applied to this problem.

This study investigates into how organizations enable the compatibility between intermediary role of conventional systems with disintermediary potentials of blockchain toward the coordination of multiple actors in operations management.

The data were collected from 31 interviewees of the case organizations. We conduct an in-depth case study of successful BC implementation in operations management, by using affordance-actualization (A-A) theory as the theoretical lens.

This study identifies the incompatibility between the affordances of conventional systems and blockchain in coordination/operations management and offers a process model in which a fusion phase enables the affordances to be compatible and then to be actualized. The fusion phase extends A-A theory by transposing and connecting in the context of operations management. The result also shows that blockchain technology has decentralized potentials to address the issues caused by centralized organizations or information systems, while not to replace the intermediary roles of centralized organizations or information systems.

This study makes important theoretical contributions to the literature on blockchain used in operations management, the roles of blockchain enablement and affordance-actualization theory. The findings can also help IT practitioners to implement BC-based applications effectively.