IIMB Management Review最新文献

{"title":"Navigating office politics: How do self-concept and upward voice influence women's workplace well-being?","authors":"Apoorva Goel ,&nbsp;Nabila Khan ,&nbsp;Lata Dyaram","doi":"10.1016/j.iimb.2024.04.001","DOIUrl":"10.1016/j.iimb.2024.04.001","url":null,"abstract":"<div><div>Using the Job Demands-Resources theory, this study examines how organisational politics and self-concept affect women employees’ voice and workplace well-being (WWB). It employs an explanatory-sequential design, with study 1 (quantitative research, n = 463) using experimental vignettes and scale measures to test the hypotheses, followed by study 2 (qualitative research, n = 12) using in-depth interviews to explain the quantitative results. It was found that women's perceptions of organisational politics debilitated their WWB mediated by their voices. Furthermore, the “relational” self-concept moderated the mediated association, which reduced the negative impact. The study goes beyond the typical conception of work-family balance to provide strategies for improving women's work experiences.</div></div>","PeriodicalId":46337,"journal":{"name":"IIMB Management Review","volume":"37 1","pages":"Article 100526"},"PeriodicalIF":1.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140769677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A set of linearised partially-parallel splitting methods for separable convex programs","authors":"Jitamitra Desai ,&nbsp;Kai Wang","doi":"10.1016/j.iimb.2024.03.001","DOIUrl":"10.1016/j.iimb.2024.03.001","url":null,"abstract":"<div><div>The proximal partially-parallel splitting method (PPSM), originally proposed in Wang, Desai, and He (2017), is a hybrid mechanism that inherits the nice properties of both Gauss-Seidel and Jacobian substitution procedures for solving the multiple-block convex minimisation problem, whose objective function is the sum of <span><math><mi>m</mi></math></span> individual (separable) functions without any shared variables, subject to a linear coupling constraint. In this paper, we extend this work and present some <em>linearised versions</em> of the PPSM, which fully utilise the separable structure and result in subproblems that either have closed-form solutions or are relatively easy to solve as compared to their original nonlinear versions. Global convergence of these linearised methods under the projection contraction algorithmic framework is proven, and furthermore, detailed remarks that serve to clarify the interconnections between these linearised variants are highlighted. Finally, the worst-case <span><math><mrow><mi>O</mi><mo>(</mo><mn>1</mn><mo>/</mo><mi>t</mi><mo>)</mo></mrow></math></span> convergence rate of these methods under ergodic conditions is also established.</div></div>","PeriodicalId":46337,"journal":{"name":"IIMB Management Review","volume":"37 1","pages":"Article 100518"},"PeriodicalIF":1.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140154320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Targeting audience personas with programmatic geographic segments using unsupervised methods","authors":"Viraj Noorithaya","doi":"10.1016/j.iimb.2025.100549","DOIUrl":"10.1016/j.iimb.2025.100549","url":null,"abstract":"<div><div>The digital advertising industry, where clients advertise to existing and potential customers through digital channels, is going through a rapid transformation. This is necessitated by evolving privacy laws such as General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA), heading towards a cookie-less future by decreasing reliance on Personally identifiable information (PII). While approaches like Data clean rooms, Federated learning have started gaining prominence, the current AdTech space is highly fragmented regarding channels, standards, platforms, inventory, cookieless targeting approaches, and compatibility.</div><div>For marketers, it is crucial to have generalized and interoperable but privacy-compliant approaches to reach their audience. While it is safer not to limit to a specific advertising stack, it must not come at a substantial performance cost. When a brand starts an advertising campaign, they usually have objectives and a target audience in mind. While their objectives are aligned with business goals and performance metrics, the desired audience personas are defined by either market research or new/ historically well-performing consumer profiles suited to their products and services. This paper presents ways to convert multi-characteristic personas into geographic targeting without relying on cookie-based data. These geographic segments have broad compatibility across marketing platforms.</div><div>We sourced data from 5 privacy-compliant datasets containing ∼9000 variables aggregated at Forward Sortation Area (FSA) level by a leading Canadian data provider. These variables span a wide range of characteristics such as demographic, econometric, lifestyle and media choices, brand affinities, purchasing behaviors, and spending. The persona-related variables are optionally indexed, after which dimensionality reduction techniques, such as Principal Component Analysis (PCA) and Uniform Manifold Approximation and Projection (UMAP), were applied. Unsupervised learning methods, such as KMeans, KMeans++ and Gaussian Mixture Models (GMMs), were then used to build an optimal number of FSA clusters. These clusters were then analyzed to identify those beneficial to targeting, which helps reduce the number of FSAs to target. The final output for marketing consumption is in the form of FSA segments for targeting aligned with our desired profiles. We analyze campaign metrics against different combinations of dimensional reduction and clustering techniques to assess what works well for advertising.</div></div>","PeriodicalId":46337,"journal":{"name":"IIMB Management Review","volume":"37 1","pages":"Article 100549"},"PeriodicalIF":1.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143593568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"War-driven attention and cryptocurrency returns: The case of the Russia–Ukraine war","authors":"Arushi Verma,&nbsp;Madhumita Chakraborty","doi":"10.1016/j.iimb.2025.100552","DOIUrl":"10.1016/j.iimb.2025.100552","url":null,"abstract":"<div><div>The paper investigates how attention to the Russia-Ukraine war affects cryptocurrency returns by creating a Google search volume index (GSVI) using Google trends keywords. It finds that crypto returns react positively to attention to war and negatively to the volatility index (VIX), demonstrating that investor fear during times of crisis may increase interest in cryptocurrencies. The research provides specific insights into crypto markets that can aid portfolio managers and regulators. It also adds to the limited studies on the impact of war on cryptocurrency returns.</div></div>","PeriodicalId":46337,"journal":{"name":"IIMB Management Review","volume":"37 1","pages":"Article 100552"},"PeriodicalIF":1.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Acknowledgement to Reviewers","authors":"","doi":"10.1016/S0970-3896(25)00017-5","DOIUrl":"10.1016/S0970-3896(25)00017-5","url":null,"abstract":"","PeriodicalId":46337,"journal":{"name":"IIMB Management Review","volume":"37 1","pages":"Article 100565"},"PeriodicalIF":1.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143696881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Organisational healing in VUCA times: A theoretical refinement","authors":"Aditya Agrawal ,&nbsp;Ashish Pandey ,&nbsp;Payal Kumar","doi":"10.1016/j.iimb.2025.100551","DOIUrl":"10.1016/j.iimb.2025.100551","url":null,"abstract":"<div><div>Organisational healing (OH), as an existing theoretical concept developed by Powley et al., refers to the process of repairing and restoring the social relationships of an organisation after any external trauma. In this study, we aim to expand the nature and application of OH by exploring additional areas of applicability. We examine the critical assumptions in the existing conceptualisation of OH and propose modifications and additions, which help make OH a more robust construct. Finally, we identify the theoretical and managerial implications of this study and discuss future research implications.</div></div>","PeriodicalId":46337,"journal":{"name":"IIMB Management Review","volume":"37 1","pages":"Article 100551"},"PeriodicalIF":1.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An innovative modelling framework for freight consolidation in transportation planning","authors":"Manoj Kumar ,&nbsp;Anoop K. P.","doi":"10.1016/j.iimb.2025.100550","DOIUrl":"10.1016/j.iimb.2025.100550","url":null,"abstract":"<div><div>This paper addresses freight consolidation in rail transportation planning. Multiple demand destinations are served in a single trip to utilise the volume discount on freight rate. An efficient mixed-integer linear programming (MILP) based modelling framework is proposed to optimally allocate rail wagons to a given set of destinations considering the shipment options offered by Indian Railways. Twelve problem instances are derived using real data from an Indian food grain organisation and are solved to optimum using the CPLEX solver in quick time. The results indicate that multi-point orders can reduce the total transportation cost and ease the handling of shipments at terminals.</div></div>","PeriodicalId":46337,"journal":{"name":"IIMB Management Review","volume":"37 1","pages":"Article 100550"},"PeriodicalIF":1.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"What elements of the opening set influence the outcome of a tennis match? An in-depth analysis of Wimbledon data","authors":"Kapil Gupta ,&nbsp;Vijayshankar Krishnamurthy ,&nbsp;Soudeep Deb","doi":"10.1016/j.iimb.2024.03.002","DOIUrl":"10.1016/j.iimb.2024.03.002","url":null,"abstract":"<div><div>This study examines the importance of game elements of the first set in Wimbledon matches in deciding the match outcome. We propose a LASSO-induced logistic regression model based on first set data to identify the variables that impact the match outcome. Our findings indicate that winning service points, average distance travelled, and rating points significantly impact match outcome. Additionally, we show the effectiveness of our proposed model in within-match forecasting during the first set, and it frequently performs better than other statistical and machine-learning approaches. We also discuss important managerial applications of our methodology for players, coaches, and other stakeholders.</div></div>","PeriodicalId":46337,"journal":{"name":"IIMB Management Review","volume":"37 1","pages":"Article 100519"},"PeriodicalIF":1.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140154323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SYNOPSES","authors":"","doi":"10.1016/j.iimb.2024.11.002","DOIUrl":"10.1016/j.iimb.2024.11.002","url":null,"abstract":"","PeriodicalId":46337,"journal":{"name":"IIMB Management Review","volume":"36 4","pages":"Pages 286-288"},"PeriodicalIF":1.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143311051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of automation of routine and non-routine tasks on labour demand and wages","authors":"Arvind Upreti,&nbsp;V. Sridhar","doi":"10.1016/j.iimb.2024.09.001","DOIUrl":"10.1016/j.iimb.2024.09.001","url":null,"abstract":"<div><div>Artificial intelligence and associated technology advances have progressively diffused from routine tasks to non-routine tasks, causing disruptions in the labour market. In this work, we study the effect of automation on the labour market outcomes for low-skilled and high-skilled workers. We use the agent-based modelling approach to model firms and workers as rational agents with defined objective functions, endowments, and interactions. Using extensive simulations, we analyse the emergent phenomenon of employment levels and wage inequality in the labour market under varying scenarios. The key findings of our simulations indicate that automation of routine tasks increases wage inequality, whereas automation of non-routine tasks reduces it. Based on our results, we propose policy prescriptions regarding the job categories in which automation can be introduced for societal benefits, the skill enhancement programme needed for the workers, and guidelines on the redeployment of labour displaced through automation.</div></div>","PeriodicalId":46337,"journal":{"name":"IIMB Management Review","volume":"36 4","pages":"Pages 289-308"},"PeriodicalIF":1.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143311049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}