Avoiding epistemological silos and empirical elephants in OM: How to combine empirical and simulation methods?

Chandrasekaran, Aravind; Linderman, Kevin; Sting, Fabian J.

doi:10.1016/j.jom.2018.11.003

Cited by 30 publications

(36 citation statements)

References 36 publications

(38 reference statements)

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“…Specifically, Chandrasekaran et al (2018) overview the latest possible uses for the combining empirical and simulation methods. Absent from their model is our use of experiments offering causal evidence of effects joined with simulation that quantify these effects on delivery operations systems (Chandrasekaran et al 2018).…”

Section: Introductionmentioning

confidence: 99%

Going Green: The Effect of Green Labels on Delivery Time Slot Choices

Agatz

Fan

Stam³

2020

SSRN Journal

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In this paper, we study the effectiveness of incentives on delivery service time slot choices. In particular, we focus on the use of green labels that specify time slot as environmentally friendly and that intrinsically motivate customers to choose a specific delivery time slot in lieu of price incentives based on extrinsic motivation. We argue this is important since green labels' intrinsic nature affects costumer choice in fundamentally different ways than price incentives. We conduct two experiments and two simulation studies to study effects of using green labels. Our experimental findings suggest that: (1) green labels are an effective tool to steer shoppers toward a certain delivery option, (2) green labels are more effective for people who are more eco-conscious, (3) green labels remain effective in the presence of price incentives, while price incentives offer little added value beyond that of just green labels, and (4) the effectiveness of green labels versus price discounts remains high when time slots are less appealing (longer). Our simulation findings suggest that green slots, compared to price incentives or no incentives, offer providers a way to effectively steer consumer time slot choices to yield shorter routes, fewer delivery vehicles used, and more per-customer revenue. We thus conclude that steering individuals to select delivery time slots through intrinsic motivation via green labels may be a promising, no-cost direction for (online) retailers and an important topic for research.

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Section: Introductionmentioning

confidence: 99%

Going Green: The Effect of Green Labels on Delivery Time Slot Choices

Agatz

Fan

Stam³

2020

SSRN Journal

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“…A single case study faces the inherent challenge of limited generalisability. Adding simulation using the system dynamics method to the empirical case analysis allowed us to explore counterfactuals (Chandrasekaran et al, 2018). Furthermore, the simulation model makes it possible to create variety in critical decisions, boundary conditions and parameters for which cannot be observed in the empirical case data.…”

Section: Methodology: a Combined‐methods Approachmentioning

confidence: 99%

“…We applaud the research development in the field of ITO. Meanwhile, we observed a strong reliance on cross‐sectional research designs in the extant literature, and studies that, due to the inherent limitation of methodology setting, often omit the fact that buyer–supplier relationships are dynamic and can change over time (Chandrasekaran, Linderman, & Sting, 2018). A static view of ITO relationships limits our understanding of how these relationships evolve into a spiral, what are the potential mechanisms to reverse this downward spiral and what are the boundary conditions of the reversal mechanisms.…”

Section: Introductionmentioning

confidence: 99%

“…We then go on to show how an action‐research intervention using collaborative service (re‐)design (CSD) on workflows was effective in reversing the direction of the vicious spirals. We then synthesise the observed dynamics in the three interlocked cycles and the reversed mechanism in a system dynamics simulation model in order to further elucidate the boundary conditions of the proposed theory established in the action research (Chandrasekaran et al, 2018; Fang et al, 2018; Sting, Stevens, & Tarakci, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Reversing a relationship spiral: From vicious to virtuous cycles in IT outsourcing

Akkermans

Oppen²,

Vos

et al. 2020

Information Systems Journal

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IT outsourcing (ITO) remains a popular business practice, but many buyers and suppliers of IT services are caught in a vicious relationship spiral of low trust, bad collaboration and mediocre performance. This paper describes a novel process understanding of how vicious cycles work and suggests a new method for how they can be reversed into virtuous cycles. Based on the action research and complementary system dynamics simulation, this paper demonstrates how an ineffective ITO relationship between a European Harbour Authority and its main IT supplier ITCo was formed and, later, transformed. The method, involving collaborative redesign of service workflows, applied in this action research triggered the reversal of an otherwise downward relationship spiral. Both the empirical facts from the action research data and the system dynamics simulation data are provided as evidence. We conclude the paper with conceptual and methodological contributions as well as scope for future research.

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“…Therefore, we design a simulation to understand the implications of our model for managerial decision‐making related to capacity setting, effort allocation, and task closure (cf. Chandrasekaran, Linderman, & Sting, ). We demonstrate that managers can adopt our recommended approach to address a larger number of tasks with a minimal lowering of the overall successful resolution rates, while improving response times.…”

Section: Introductionmentioning

confidence: 99%

Managing uncertain tasks in technology‐intensive project environments: A multi‐method study of task closure and capacity management decisions

Narayanan

Balasubramanian

Swaminathan

et al. 2019

J of Ops Management

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Engineers working on tasks in technology‐intensive project environments face substantial task resolution uncertainty. This can result in poor capacity utilization as they expend effort on tasks that are not successfully resolved. A deeper understanding of task‐related uncertainty can help the firm optimize effort allocation across tasks by implementing well‐designed task closure policies that facilitate superior capacity utilization and capacity planning. In this article, we characterize the empirical distribution of task uncertainty and demonstrate how the resolution process affects task outcomes in project environments. Using a combination of empirical estimation, and analytical and simulation modeling, we develop insights into task‐related decision‐making and engineer effort allocation. Using real‐world task resolution data from a software maintenance setting, we first model and estimate a beta‐geometric survival distribution which indicates that the likelihood of successful task resolution substantially reduces with the time a task remains in the system. Using analytical and simulation modeling, we then examine the implications of imposing task closure policies to improve engineer effort allocation and increase system productivity. We demonstrate that adopting well‐designed task closure policies can significantly improve engineer resource utilization in capacity‐constrained settings without a substantial negative impact on project outcomes. We discuss the implications of our research for theory and practice.

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Avoiding epistemological silos and empirical elephants in OM: How to combine empirical and simulation methods?

Cited by 30 publications

References 36 publications

Going Green: The Effect of Green Labels on Delivery Time Slot Choices

Going Green: The Effect of Green Labels on Delivery Time Slot Choices

Reversing a relationship spiral: From vicious to virtuous cycles in IT outsourcing

Managing uncertain tasks in technology‐intensive project environments: A multi‐method study of task closure and capacity management decisions

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