Management and Marketing - Research Publications

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    A brighter vision of the potential of open science for benefiting practice: A ManyOrgs Proposal
    Castille, CM ; O'Boyle, E ; Köhler, T (Cambridge University Press, 2022-08-30)
    Guzzo et al. (2022), in their focal article express concerns that rewarding open science practices, particularly in scholarly publishing, may harm the practical relevance of our research. They go on to urge greater reliance on conceptual replication over direct or exact replication to verify claims in our field. Although we concur with the majority of their recommendations, their prescriptions nevertheless do not fully address the deeper issue of publication and outcome reporting bias traceable to insufficient resources. Other sciences have effectively addressed this resource problem via crowdsourcing, large-scale collaborations, and multi-site replication (both conceptual and direct). Such initiatives are a pragmatic, if challenging to implement, solution to problems that face many areas of science such as ours (e.g., ensuring sufficient statistical power, assessing the generalizability and replicability of effects, spurring the uptake of open science practices, promoting diversity and inclusivity). Here, we propose that IO psychologists create such an initiative that primarily services practice. We tentatively call this initiative ‘ManyOrgs’. We also clarify how this open science initiative complements Guzzo et al.
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    A brighter vision of the potential of open science for benefiting practice: A ManyOrgs Proposal
    Castille, C ; Koehler, T ; O'Boyle, E (Cambridge University Press, 2022)
    Guzzo et al. (2022), in their focal article express concerns that rewarding open science practices, particularly in scholarly publishing, may harm the practical relevance of our research. They go on to urge greater reliance on conceptual replication over direct or exact replication to verify claims in our field. Although we concur with the majority of their recommendations, their prescriptions nevertheless do not fully address the deeper issue of publication and outcome reporting bias traceable to insufficient resources. Other sciences have effectively addressed this resource problem via crowdsourcing, large scale collaborations, and multi-site replication (both conceptual and direct). Such initiatives are a pragmatic, if challenging to implement, solution to problems that face many areas of science such as ours (e.g., ensuring sufficient statistical power, assessing the generalizability and replicability of effects, spurring the uptake of open science practices, promoting diversity and inclusivity). Here, we propose that IO psychologists create such an initiative that primarily services practice. We tentatively call this initiative ‘ManyOrgs’. We also clarify how this open science initiative complements Guzzo et al.
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    More partisans than parachutes, more successful than not: Indigenous candidates of the major Australian parties
    Evans, M ; McDonnell, D (ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD, 2022-04-28)
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    Save Your Wardrobe: Supporting Sustainable and Mindful Clothing Consumption
    Scaraboto, D ; Shaw, D ; Duffy, K (Walter de Gruyter GmbH, 2022-05-01)
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    Evaluating sustainably resilient supply chains: a stochastic double frontier analytic model considering Netzero
    Azadi, M ; Kazemi Matin, R ; Emrouznejad, A ; Ho, W (Springer Science and Business Media LLC, 2022-01-01)
    Abstract In era of reglobalization, sustainably resilient supply chains (SCs) are imperative in corporations to improve performance and meet stockholders’ expectations. However, sustainably resilient SCs could not be effective if are not assessed by using advanced frameworks, systems, and models. As such, developing a novel network data envelopment model (DEA) to appraise sustainably resilient SCs is our purpose in this article. To do so, we present a new double-frontier methodology to provide optimistic and pessimistic efficiency measures in network structures. Moreover, ideas of outputs weak disposability, chance-constrained programming, and discrete dominance are incorporated in a unified framework of modelling efficient and inefficient production technologies. The new network DEA model also can address dissimilar types of data, including undesirable and integer-valued and ratio outputs, stochastic intermediate products, and integer-valued inputs in a unified framework. Furthermore, an aggregated Farrell type efficiency measure is developed which allows to provide the complete ranking of units so that each decision-making unit (DMU) has its own rank in both overall and divisional point of view. We show the unique features of our developed model using a real case study in paint industry to evaluate the efficiency and reducing carbon dioxide (CO2) emissions. The results show that how well the proposed models can evaluate the sustainability and resilience of supply chains in the presence of uncertainty and with dissimilar types of data.
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    An analytic network process model to prioritize supply chain risks in green residential megaprojects
    Alamdari, AM ; Jabarzadeh, Y ; Adams, B ; Samson, D ; Khanmohammadi, S (SPRINGER, 2022-06-22)
    Abstract Megaprojects and specifically ‘green’ construction of residential megaprojects can contain significant risks of failure. To design proper risk mitigation strategies, after identifying key risk factors, the next step is to conduct assessments that would facilitate the process of risk element prioritization. Risk assessment comprises the establishment of factor interrelation and discerning the indicators of importance. This research proposes a novel version of an integrated prioritization method and analyzes twelve all-inclusive key supply chain oriented risk factors identified in a previous study. Through a comprehensive literature review three criteria, impact, probability, and manageability are selected. Also, a fourth criterion namely influence rate is included in the model, based on the driving powers that can also be derived from the Interpretive Structural Modeling’s (ISM) assessment. Fundamentally, the calculations hinge on the Analytic Network Process (ANP) method which provides an assessment of the alternatives’ weights based on pairwise comparisons concerning the criteria specified. To enhance the accuracy of the perceptive judgments of the expert panelists, a bell-shaped fuzzy function is used to convert the verbal statements to crisp values. In addition, Row Sensitivity Analysis is administered to check the stability of the results and provide predictive scenarios. To validate the model, a case study, located in Iran, was conducted, where an expert panel consisting of four individuals made the pair-wise comparisons through an ANP questionnaire. Results indicate priority and sensitivity of the alternatives concerning criteria, for the case under study.
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    Blockchain as the "trust-building machine" for supply chain management
    Yavaprabhas, K ; Pournader, M ; Seuring, S (SPRINGER, 2022-08-05)
    UNLABELLED: This paper aims to investigate the impact of blockchain application on trust levels in supply chains. Through the systematic review of the relevant literature, three dimensions of trust, i.e., the trustor-trustee perspective, forms of trust, and time orientation, are investigated. Our findings show that, first, there are three pairs of trustors and trustees involved in blockchain implementation: (a) the user and the blockchain, (b) two supply chain partners, and (c) the consumer/public and a supply chain unit. Second, the two forms of trust, namely cognition-based and institution-based trust, are likely to be enhanced by blockchain execution, while affect-based trust may not be directly impacted by the technology. Third, the presence of blockchain technology would facilitate swift trust-building between unknown supply chain partners under specific circumstances. Moreover, we also find contradicting assertions among scholars on the implications of blockchain for trust in supply chains. While some studies pointed out that blockchain will enable a trustless trusted scheme, others expected the reinforcement of interorganizational trust. To test these assertions, we develop the blockchain-entrusted supply chain models to present the three-step process of how trust is developed through the blockchain and diffused to supply chain partners and external stakeholders. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10479-022-04868-0.
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    Competitive Multiproduct Contracting Under Multinomial Logit Demand
    Shao, L (Wiley, 2022-08-23)
    Despite the prevalence of multiproduct firms in many industries, the supply chain contracting literature has predominantly focused on problems where an upstream player offers only one product. This paper studies multiproduct contract design for competing manufacturers each with several products to sell via a common retailer. We consider two contracting schemes under multinomial logit demand (MNL): individual contracting, in which the manufacturers set a wholesale price for each of their products separately; and aggregate contracting, in which the manufacturers set the price as a function of the order quantities for their own products. We find that under individual contracting it is optimal for each manufacturer to offer the full range of his products to the retailer and set an equal wholesale margin for these products. This suggests that the classic result of an equal-margin policy for the retailer also holds true for the manufacturers. Further, there is an equilibrium characterized by a system of nonlinear equations that can be solved using the standard bisection search method. Under aggregate contracting, a simple cost-plus contract is optimal for the manufacturers. In equilibrium, each manufacturer charges a markup equal to his marginal contribution to the supply chain, and the supply chain profit is maximized. Comparing these two contracting schemes, we find among other results that the retailer prefers aggregate contracting when there is a large number of products from each manufacturer or when consumer heterogeneity is low, while the opposite is true for the manufacturers. In addition, both the retailer and the manufacturers prefer aggregate contracting when there are few manufacturers in the supply chain. It is also found that as the number of manufacturers or the number of products from each manufacturer increases, the supply chain efficiency loss induced by individual contracting is reduced. Finally, we extend our model to a hybrid setting in which one manufacturer adopts aggregate contracting and the other adopts individual contracting, and demonstrate to the manufacturers the value of aggregate contracting. These results provide useful guidance on optimal contract design for multiproduct firms.
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    A Capacity Reservation Game for Suppliers with Multiple Blocks of Capacity
    Shao, L (Elsevier, 2022-09-01)
    This paper studies a supplier competition model in which a buyer reserves capacity from a number of suppliers that each have multiple blocks of capacity (e.g., production or power plants). The suppliers each submit a bid that specifies a reservation price and an execution price for every block, and the buyer determines what blocks to reserve. This game involves both external competition between suppliers and internal competition between blocks from each supplier. We characterize the properties of pure-strategy Nash equilibria for the game. Such equilibria may not always exist, and we provide the conditions under which they do.
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    A transformative service research perspective on caste-based discrimination in microcredit lending in India
    Meshram, K ; Venkatraman, R (EMERALD GROUP PUBLISHING LTD, 2022-06-29)
    Purpose: This research aims to address the transformative service research (TSR) agenda by examining the issue of caste-based financial exclusion in microcredit lending services in India. To do so, it draws on statistical discrimination theory from labour economics to develop and test a multi-level prosocial service orientation framework. Design/methodology/approach: Survey data come from 238 loan officers and 250 lower caste loan applicants across 43 microfinance institutions (MFIs) in India. The data are analysed using hierarchical linear modelling, a method appropriate for investigating micro- and macro-level organisational variables. Findings: At the micro level, the service orientation factors of social dominance orientation and algorithmic-driven lending decisions affect financial exclusion of lower caste bottom-of-the-pyramid (BoP) vendors. At the macro level, the service orientation mechanism of inclusive service climate reduces caste-based financial exclusion, while the level of lending risk to reduce discrimination receives no support. Research limitations/implications: Research in other contexts is warranted to confirm the prosocial service orientation model. Methodological challenges at the BoP also present avenues for insightful work. Social implications: The study shows the importance of an inclusive service climate and reassessment of algorithmic-driven lending decisions to eliminate caste-based indicators in lending decisions. It also recommends policy reform of caste-based affirmative action at the macro- and micro-levels of lending decisions. Originality/value: This research extends the TSR agenda to include caste-based discrimination in prosocial services. It takes a multidisciplinary perspective on services research by incorporating statistical discrimination theory from labour economics to extend understanding of service orientation.