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Cardiovascular risk; Myocardial insulin resistance; Non-alcoholic fatty liver disease Riesgo cardiovascular; Resistencia a la insulina del miocardio; Enfermedad del higado graso no alcoholico Risc cardiovascular; Resistència a la insulina del miocardi; Malaltia del fetge gras no alcohòlic Background: We report that myocardial insulin resistance (mIR) occurs in around 60% of patients with type 2 diabetes (T2D) and was associated with higher cardiovascular risk in comparison with patients with insulin-sensitive myocardium (mIS). These two phenotypes (mIR vs. mIS) can only be assessed using time-consuming and expensive methods. The aim of the present study is to search a simple and reliable surrogate to identify both phenotypes. Methods: Forty-seven patients with T2D underwent myocardial [18F]FDG PET/CT at baseline and after a hyperinsulinemic–euglycemic clamp (HEC) to determine mIR were prospectively recruited. Biochemical assessments were performed before and after the HEC. Baseline hepatic steatosis index and index of hepatic fibrosis (FIB-4) were calculated. Furthermore, liver stiffness measurement was performed using transient elastography. Results: The best model to predict the presence of mIR was the combination of transaminases, protein levels, FIB-4 score and HOMA (AUC = 0.95; sensibility: 0.81; specificity: 0.95). We observed significantly higher levels of fibrosis in patients with mIR than in those with mIS (p = 0.034). In addition, we found that patients with mIR presented a reduced glucose uptake by the liver in comparison with patients with mIS. Conclusions: The combination of HOMA, protein, transaminases and FIB-4 is a simple and reliable tool for identifying mIR in patients with T2D. This information will be useful to improve the stratification of cardiovascular risk in T2D. This work was supported by the Carlos III Health Institute and the European Regional Development Fund (PI16/02064, PI20/01588) and the Agency for Management of University and Research Grants (AGAUR) of Catalonia (2017SGR1303).

We motivate and implement an Artificial Intelligence (AI) Computer Aided Diagnosis (CAD) framework, to assist clinicians in the early diagnosis of Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD). Our framework is based on a Convolutional Neural Network (CNN) trained and tested on functional Magnetic Resonance Images datasets. We contribute to the literature on AI-CAD frameworks for AD by using a 2D CNN for early diagnosis of MCI. Contrary to current efforts, we do not attempt to provide an AI-CAD framework that will replace clinicians, but one that can work in synergy with them. Our framework is cheaper and faster as it relies on small datasets without the need of high-performance computing infrastructures. Our work contributes to the literature on digital transformation of healthcare, health Information Systems, and NeuroIS, while it opens novel avenues for further research on the topic.

Access to adequate working capital is often a challenge for SMEs, especially if SME faces the risk of an uncertain yield. We identify conditions under which a strong buyer should either offer “backing” or guarantee for the purchase-order finance for a cash-constrained, risky SME supplier, or end the relationship. By offering a backing, buyer shares the default risk faced by the bank, in order to keep the SME supplier in business. To identify the possible benefits of this scheme, we compare the buyer’s operational and financial decisions under three financing mechanisms: buyer-backed purchase order financing, purchase order financing with no backing and purchase order financing with a fixed buyer-backing. The non-linear optimization problem is solved using KKT optimality conditions and sufficiency is established through invexity. We perform numerical experiments for all the models for different levels of yield risks of the supplier. We are able to separate conditions to suggest when (1) no backing is required; (2) when backing should be offered to sustain the supplier, and (3) when an alternative supplier should be located.We find that backing has the following benefits: buyer can use backing as a substitute to higher purchase price; it helps the supplier to stay operative till a higher shock level; shared risk of default leads the bank to offer financing at a lower rate; finally resulting in consistently higher buyer profits despite the added risk. The separation condition as described above can also be used by managers to compare two suppliers.

Truck congestion at chemical sites is a persistent problem that is difficult to solve, even using a truck appointment system. This study presents an alternative solution to improve the flexibility of chemical sites by creating a drop-swap terminal adjacent to the site location. The terminal serves as an intermediate depot where the trucks can drop empty containers and swap them with preloaded containers without entering the site. This study aims to evaluate the performance of such a solution in mitigating truck congestion at chemical sites. The problem is modeled as a nonstationary semi-open queueing network with time-varying arrivals. We propose a combination of a fluid-flow approximation and a decomposition-aggregation method to estimate the time-dependent performance of the system. A chemical site in the Netherlands is presented as a case study. Several scenarios are tested and evaluated. Numerical results show that a drop-swap terminal can effectively reduce truck idling time and increase logistics efficiency at chemical sites. We also found that swapping containers on chassis is a cheaper and greener option to operate the terminal. However, the investment needed to support the operation should not be overlooked to sustain the benefits. The study concluded with several key messages for site operators who wish to maximize the benefit from a drop-swap terminal.

Based on the communicative ecology framework and theories related to guanxi and communication context in China, we investigate the moderating effects of individual preference for communication context (IPCC) on knowledge sharing via interactive systems (KSIS) behavior. Drawing on survey data from a hotel chain's employees, we explore how guanxi elements drive knowledge sharing (KS) behavior and enhance KS outcomes. Our data demonstrate that IPCC significantly moderates the effect that KSIS has on KS outcomes, but the IPCC has a direct and negative impact on KS outcomes. We explain these seemingly contradictory findings and their implications for research and practice.

In this paper, we study the influence of seasonal demands and forecasts on the performance of an Automatic Pipeline, Variable Inventory, Order-Based, Production Control System (APVIOBPCS) using linear control theory. In particular, we consider a system that uses a seasonal forecast based on a no-trend, additive-seasonality exponential-smoothing model, and compare its performance to an equivalent system using simple exponential smoothing. We find that the system with seasonal forecasting significantly outperforms the system with simple exponential smoothing under certain demand assumptions. With optimal parameter settings, the forecast error of the seasonal model can be up to 40% lower. However, we also find that the forecast superiority does not necessarily translate to the performance of the system measured through the bullwhip metrics. In addition, the seasonal forecasting model is very sensitive to the demand frequency and smoothing parameters, while the simple exponential smoothing model is very robust. This implies that the real life benefits of implementing a seasonal forecasting model are not obvious and depend on the particular situation; under a large number of settings (e.g. low seasonality, high-smoothing), the good performance of simple exponential smoothing certainly justifies its popularity in the industry and research worlds alike.

Problem definition: Online retailers are on a consistent drive to increase on-time delivery and reduce customer lead time. However, in reality, an increasing share of consumers places orders early. Academic/practical relevance: Such advance demand information can be deployed strategically to reduce costs and improve the customer service experience. This requires inventory and allocation policies that make optimal use of this information and that induce consumers to place their orders early. An increasing number of online retailers not only offer customers a choice of lead time but also, actively back-order missing items from a consumer basket. Methodology: We develop new allocation policies that commit to a customer order upon arrival of the order rather than at the moment the order is due. We provide analytical results for the performance of these allocation policies and evaluate their behavior with real data from a large food retailer. Results: Our policy leads to a higher fill rate at the expense of a slight increase in average delay. The analysis based on real-life data suggests a sizeable impact that should impact current best practices in online retail. Managerial implications: With the changing landscape in online retail, customers increasingly place baskets of orders that they would like to receive at a planned and confirmed moment in time. Especially in grocery, this has grown fast. This fundamentally changes the strategic management of inventory. We demonstrate that online retailers should commit early to customer orders to enhance the customer service experience and eventually, to also create opportunities for reducing the cost of operations. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.1124 .

PurposeThis study aims to investigate how technology characteristics facilitate employees' work meaningfulness through job crafting.Design/methodology/approachThis study applies the survey method and collects data from 357 Chinese participants with the experience of using information technology (IT) at work.FindingsTechnology characteristics (i.e. technology reconfigurability and technology customization) enable employees to craft their jobs, contributing to work meaningfulness.Research limitations/implicationsIt remains to be seen whether the findings can be generalized to other cultural contexts. This study justifies the positive effects of IT but does not take into consideration the IT factors that might thwart job crafting.Practical implicationsIT is not merely a work tool. It is a contextual component strongly conducive to cultivating work meaningfulness. However, IT itself cannot directly lead to work meaningfulness. Instead, its contribution to job crafting matters.Originality/valueThe literature on the downstream impact of IT has yet to consider the value of IT for job crafting and work meaningfulness. This study verifies that job crafting is the linking mechanism between IT and work meaningfulness.

Vertical equity or fairness is an important aspect in many settings, yet has received relatively little attention in the literature. Recent developments underline the practical relevance (e.g., COVID-19 vaccination policies). It plays an important role in the performance evaluation of many (nongovernmental) organizations. For example, donors might require a family-planning organization to allocate a minimum fraction of the total utility (client volume) to a particular player (the “high-impact” subgroup of the population, e.g., young and poor clients). However, the price (decrease in client volume) of such requirements is not well-understood. Consequently, this price is not accounted for in decision making. We provide an analytical upper bound on the price (i.e., loss of overall utility) of vertical equity considerations in resource allocation. We assume that these concerns are expressed via outcome constraints, specifying a minimum percentage of the total utility for each player. Our set-up considers a decision maker maximizing total utility over a general convex set, subject to outcome constraints. The set-up is general and applicable to many practical problems. Our results depend only on high-level parameters and are therefore well-suited for strategic decision making. We conclude with two applications. First, we apply our results to practical instances in health delivery. We confirm that outcome constraints can entail a substantial price and analyze the factors driving this price close to the worst-case bound. Second, we analyze how our results can help bound the impact of prioritization in vaccine allocation. This paper was accepted by Jeannette Song, operations management. Supplemental Material: Data files are available at https://doi.org/10.1287/mnsc.2021.4287 .

With the advent of responsible business, ensuring social responsibility in sourcing is of interest to both academics and practitioners. In this study, we examine one way of achieving this goal: ethical sourcing initiatives (ESIs). ESIs refer to a firm’s formal and informal actions to manage sourcing processes in an ethical and socially responsible manner. While ESIs have been established as an important part of corporate social responsibility, it is unclear whether, how, and when this corporate effort is economically beneficial. We conduct an event study estimating the shareholder value effect of 159 publicly traded firms’ ESIs and find that the stock market reacts positively to ESIs in general. We also compare market reactions under different conditions including reactive versus proactive ESIs, and their interactions with initiative timing, firm size, and financial risk. Additionally, we find that ESIs are associated with long-term stock price and operating performance. Overall, our findings clarify the potential economic benefits of corporate ESIs and encourage buying firms to take these initiatives selectively according to business contexts.

BackgroundTransitioning from paediatric medical care to adult care is a challenging process for children, parents and healthcare professionals. The aim of this study was to explore the experiences, concerns and needs of parents of children with Down syndrome and of professionals regarding this transition.MethodA qualitative study was performed using semi-structured interviews with 20 parents of children with Down syndrome and six healthcare professionals.ResultsWe showed that parents and professionals have concerns during each of the three distinct phases of transition (preparation, transfer and integration). Data disclose specific concerns regarding communication, continuity of care and rebuilding trust. We propose a framework for the transition to adult care.ConclusionsThe transition in medical care for children with Down syndrome should be flexible, patient-centred and coordinated together with patients and parents. Only in ensuring continuity of care will individuals with Down syndrome not get lost in transition.

Introduction: Real-world vaccine effectiveness (VE) estimates are essential to identify potential groups at higher risk of break-through infections and to guide policy. We assessed the VE of COVID-19 vaccination against COVID-19 hospitalization, while adjusting and stratifying for patient characteristics. Methods: We performed a test-negative case-control study in six Dutch hospitals. The study population consisted of adults eligible for COVID-19 vaccination hospitalized between May 1 and June 28, 2021 with respiratory symptoms. Cases were defined as patients who tested positive for SARS-CoV-2 by PCR during the first 48 h of admission or within 14 days prior to hospital admission. Controls were patients tested negative at admission and did not have a positive test during the 2 weeks prior to hospitalization. VE was calculated using multivariable logistic regression, adjusting for calendar week, sex, age, comorbidity and nursing home residency. Subgroup analysis was performed for age, sex and different comorbidities. Secondary endpoints were ICU-admission and mortality. Results: 379 cases and 255 controls were included of whom 157 (18%) were vaccinated prior to admis-sion. Five cases (1%) and 40 controls (16%) were fully vaccinated (VE: 93%; 95% CI: 81 - 98), and 40 cases (11%) and 70 controls (27%) were partially vaccinated (VE: 70%; 95% CI: 50-82). A strongly protective effect of vaccination was found in all comorbidity subgroups. No ICU-admission or mortality were reported among fully vaccinated cases. Of unvaccinated cases, mortality was 10% and 19% was admitted at the ICU. Conclusion: COVID-19 vaccination provides a strong protective effect against COVID-19 related hospital admission, in patients with and without comorbidity. (C) 2022 The Authors. Published by Elsevier Ltd.

We analyze the relationship between unemployment and the supply of online labor for microtasking. Using detailed US data from a large microtasking platform between 2011 and 2015, we study the participation and the number of hours supplied by workers in the US. We find that more individuals registered on the platform and completed microtasks as the unemployment level in the commuting zone increased. This effect was strongest in regions with a high share of low-skill workers. Our analyses of the intensive margin, the wage elasticity, and the temporal work patterns suggest that the increased participation was likely motivated by an effort to substitute income. Our findings suggest that microtasking platforms appear to be an interesting online labor market for less educated workers. However, we also observe very low retention rates, indicative of a solely transient participation effect.

Platforms choose between offering exclusive deals or uniform prices to content providers in a setting where content providers can multi-home or single-home. We find that platforms offer exclusive deals for sufficiently large or sufficiently small values of standalone benefits. For sufficiently large or small standalone benefits, there are relatively large or small proportion of multi-homers to single-homers, exclusive deals allow to extract more efficiently from the content provider type that is relatively large in the market. Hence, it becomes more lucrative to employ exclusive deals regardless of the pricing strategy chosen by rival platform. We find that for standalone benefits being sufficiently small, exclusive deals equilibrium is also the industry profit enhancing outcome. On the other hand, when standalone benefits are large, exclusive pricing deals equilibrium leads to a prisoner’s dilemma type of outcome.

In most dense urban environments in emerging markets, retail deliveries are very fragmented to thousands of nanostores. It is not uncommon for a delivery route to include more than 60 stops. Unloading bays are often blocked by regular traffic. Due to the complex urban environment, it is difficult to estimate the benefits of making unloading bays available. In this study, we conduct a field experiment in an urban field lab of one square kilometer in the downtown of Querétaro, Mexico. During the treatment period of one week, we obtain help from the local traffic police to keep the unloading bays available for unloading only. Using advanced GPS devices and extensive manual field observations, we are able to capture the change in driver behavior and the direct efficiency increases. We find a high efficiency gain, not only in travel time (39%) but also – remarkably – in the total time parked (17%). Corrected for other effects, we estimate a gain of about 44% in total time per delivery. Apart from the insights on unloading benefits, we also provide insights into the method of field experimentation in such a complex environment.

Artificial Intelligence (AI) is an integral part of Society 5.0. Increasingly large companies are using AI technology to promote digital transformation and assist the human resource management (HRM) process to achieve sustainable talent development. Talent intelligent management system (TIMS), as a typical hybrid intelligent system, brings both opportunities and challenges to the transformation of HRM. Although the use of TIMS has met the expectation of Society 5.0 on replacing repetitive work by digital technology, practical insights are needed to address the potential challenges in human replacement, tacit knowledge of managers and data-driven recommendations, and low interpretability of TIMS recommendations. This article outlines possible solutions to cope with the above challenges. This article shows that the challenges brought by TIMS can be solved by different mechanisms, which cover improving users' trust in TIMS, balancing the rational results and irrational emotions, and enhancing the interpretability of AI algorithms.

When demand exceeds available inventory, suppliers ration their inventory among customers (e.g., retail channels). While there are quantitative methods to facilitate these choices, in practice, humans play an important role in making final decisions that affect allocation efficiency. How do inventory risk and contractual differences (i.e. payment schemes) behaviorally affect allocation decisions when there is scarcity? We study inventory allocations between two retail channels: a high value channel with risk, and a low value channel without risk. The retail channels may also differ in terms of the timing and type of payments that take place. We develop theoretical predictions from behavioral models based on risk aversion, loss aversion, and mental accounting and test these through incentivized controlled laboratory experiments. When profit differences between channels are medium to large, subjects allocate significantly less inventory than the expected–profit–maximizing quantity to the risky, yet more profitable, channel and subjects with stronger risk appetite allocate larger quantities to the risky channel. More interestingly, risk appetite moderates the effect of the timing and type of payments on allocations in these settings. When profit differences between channels are small, the effect of risk appetite depends on the timing of payments. Overall, the possibility of experiencing negative payments (e.g., through buy–backs) reduces allocated quantities across settings. Our insights can inform planner assignment to tasks but also the design of support systems that provide information to planners who make allocation decisions.

The rising popularity of non-fungible tokens (NFTs) has led to an increase in the costs of minting digital assets into NFTs. This presents a threat for marketplaces that wish to attract NFT creators. To address this, some platforms allow creators to mint NFTs for free (lazy minting). Although this option is preferred by many, it remains unclear what the impact of lazy minting is on the market. In this work, we use data from Rarible to investigate how work quality is affected after lazy minting is introduced. We find that after the introduction, average market quality reduces by about 13.6%, while we estimate that existing creators who shift towards lazy minting reduce their work’s quality by about 8%. We further estimate that lazy minted tokens receive fewer likes compared to other similar tokens. We discuss how we contribute to the literature and how we plan to extend our work.

Refurbishing has promising economic potential, yet firms remain wary of its potential cannibalization effect on new product sales. Firms need to make strategic choices in competitive settings, involving varying brand strengths and collection constraints. The current study provides an empirical characterization of consumer behavior in such complex settings, which in turn informs an analytical model of optimal pricing policies. The results show that cannibalization (or switching) in a competitive environment has a linear relationship with price discounts, unlike the inverted U-shaped relationship observed in monopolistic settings. The experimental results also highlight the relevance of cross-cannibalization, especially for weaker firms (with low brand value) that compete with stronger firms to sell refurbished products. Our subsequent analytical results reveal how both competitors should adjust their refurbished product prices when internal and cross-cannibalization coefficients change. Weaker firms should focus on surpassing stronger competitors in terms of collection and refurbishing efforts, which implies a predominant focus on operations. Finally, we show that refurbished product prices are a function of, and profits are concave in relation to, the number of core products collected by firms.

In most platform environments, the exclusive provision of premium content from leading creators (superstars) is used as a strategy to boost user participation and secure a competitive edge vis-à-vis rivals. In this article, we study the impact of superstar exclusive content provision on platform competition and complementors’ homing decisions. Two competing platforms facilitate interactions between consumers and suppliers, of which the latter are identified by the superstar and a fringe of complementors (e.g., independent developers, amateurs). When platform competition is intense, more consumers become affiliated with the platform favored by superstar exclusivity. This mechanism is self-reinforcing as it generates an entry cascade of complementors, and some complementors single home on the favored platform. We find that cross-group externalities are key in shaping market outcomes. First, exclusivity benefits complementors and might make consumers better off when cross-group externalities are large enough. Second, contrary to conventional wisdom, vertical integration (platform-superstar) may make exclusivity less likely than vertical separation under reasonable conditions. Finally, we discuss implications for the strategies of platform owners, managers of superstars and complementors, and antitrust enforcers. This paper was accepted by Joshua Gans, business strategy. Funding: L. Madio gratefully acknowledges financial support from the Economic and Social Research Council [Grant ES/J500215/1], the UCLouvain “Move-in” Fellowship Programme, the European Research Council under the European Union’s Horizon 2020 Research and Innovation Programme [Grant 670494], and the Unicredit & Universities Foscolo Europe Fellowship. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2023.4720 .

Making deliveries of Fast-Moving Consumer Goods (FMCG) to small retailers in dense areas is a challenge. This has different levels of impact between high-income and low-income neighborhoods. They are more evident in megacities in developing countries, where there is a clear division between classes. On the one hand, governments do not attend low-income neighborhoods where there are many unsafe areas, lack of planning, and infrastructure that hinders FMCG deliveries. On the other hand, traffic regulations in high-income neighborhoods make delivery processes more complex. This paper aims to analyze urban logistics, comparing low- and high-income areas in Sao Paulo city taking into account local markets, consumer buying behavior, and the distribution process. To achieve this, a questionnaire in loco was applied to the stakeholders involved (consumers, small retailers, and carriers). The data were analyzed by using descriptive statistics. The results from small retailers, consumers, and carriers reveal that in their point of view the delivery of products is different between Base of the Pyramid (BOP) and high-income consumers (HIC). Factors such as ‘time window regulation’ and ‘infrastructure of neighborhoods’ hinder the delivery of products from companies to small retailers in regions of HIC, while in BOP regions small retailers' security and infrastructure are the major problems from the point of view of the actors. Consumer behavior poses an important factor to guide urban freight transport planning in both regions.

Product review platforms in online marketplaces differ with respect to the granularity of product quality information they provide. While some platforms provide a single overall rating for product quality (also referred to as the single-dimensional rating scheme), others provide a separate rating for each individual quality attribute (also referred to as the multidimensional rating scheme). The multidimensional rating scheme is superior to the single-dimensional rating scheme, ceteris paribus, in reducing consumers’ uncertainty about product quality and value. However, we show that, when sellers respond to product ratings by adjusting their prices, compared to the single-dimensional rating scheme, the multidimensional rating scheme does not always benefit consumers, nor does it necessarily benefit sellers or society. The uncertainty associated with quality attribute rating and the extent of differentiation between competing products determines whether a finer-grained multidimensional rating scheme is superior to a coarser-grained single-dimensional rating scheme from the consumer, seller, and social planner perspectives. The main driver of the results is that more (less) granular and less (more) uncertain information exposes (hides) underlying differentiation, or a lack thereof, between competing products, which, in turn, alters upstream price competition in the presence of heterogeneous consumer preferences. The results demonstrate that focusing on the information transfer aspect of rating schemes provides only a partial understanding of the true impacts of rating schemes.

Smart Contracts enable the automated execution of exchanges on the blockchain. From an ontological perspective, smart contracts create and automate the fulfillment of social commitments between actors. Whereas traditional deontic logic is used to make a legal determination in contractual multi-actor interactions, this paper focuses on the consequences of these actions resulting from that determination, thereby shifting the focus from monitoring to execution. The interactions between actors and the consequences in terms of commitments have not yet been formalized for smart contracts. The perspective of smart contracts is interesting, since they are considered to be autonomous agents, able to generate automated actions. We use the Event Calculus as a formal logic to represent and reason about the effects of these automated actions and the resulting commitments. Since the Event Calculus deals with local events and the consideration of time, this approach enables the uniform representation of commitments, including their operations and reasoning rules.

Problem definition: We consider a resource allocation problem faced by health and humanitarian organizations deploying mobile outreach teams to serve marginalized communities. These teams can provide a single service or an assortment of services during each visit. Combining services is likely to increase operational efficiency but decrease the relative benefit per service per visit, as operations are no longer tailored to a single service. The aim of this study is to analyze this benefit-efficiency trade-off. Academic/practical relevance: Increased operational efficiency will enable organizations to serve more people using fewer resources. This is important given the increasing funding gap organizations are facing. Our work adds to the literature on resource allocation problems and visit allocation problems specifically, where the focus has been primarily on single services. Methodology: We analyze a general visit allocation problem incorporating demand distribution (where to go) and return time (how frequently to go). We derive analytical bounds for the benefit-efficiency trade-off, and propose visit allocation policies with worst-case optimality guarantees. Results: Our results show the benefit-efficiency trade-off can be assessed based on high level parameters. We show demand alignment is a key driver of this trade-off. We apply our results to Praesens Care, a social enterprise start-up developing mobile diagnostic laboratories, and verify our insights using real-world data. Managerial Implications: Our research contributes to the discussion on innovation and increased efficiency in health and humanitarian aid delivery by quantifying operational trade-offs in offering assortments of services. Specifically, our results help assess the potential of integrated models for health and humanitarian aid delivery and provide organizations with easy-to-implement methods to determine close-to-optimal visiting policies. Importantly, our methods remain applicable in case of limited data, making them suitable for strategic decision-making.

In recent years, academics and health and humanitarian organizations are calling for ‘people-centered’ approaches, making beneficiaries’ preferences central to decisions making. While substantial progress has been made in capturing beneficiaries’ needs in resource allocation models, the approach to equity remains essentially ‘top-down’. That is, while diversity in needs is captured, the diversity in equity perceptions is not acknowledged. In this article, we argue there is a need for a complementary ‘bottom up’ view on equity, taking the perspective of the beneficiary. This will help academics and organizations to better account for the diversity in culture, experience, and social status present in most beneficiary populations. We present the 3P framework (People, Past, and Present) to help systematically think of drivers of beneficiaries’ distributional preferences. Furthermore, we illustrate how these preferences can be integrated into utility-based modeling and why accounting for preferences is important.

Background Healthcare professionals caring for chronically ill patients increasingly want to provide patient-centered care (PCC). By understanding each individual patient journey, they can significantly improve the quality of PCC. A patient journey consists of patient interactions, so-called touchpoints, with healthcare professionals distributed over three periods: pre-service, service, and post-service period. The aim of this study was to ascertain chronically ill patients’ needs for digital alternatives for touchpoints. Specifically, we aimed to explore which digital alternatives patients would like to see implemented into their patient journey to help healthcare professionals providing PCC. Methods Eight semi-structured interviews were conducted either face-to-face or via Zoom. Participants were included if they had visited the department of internal medicine and had received treatment for either arteriosclerosis, diabetes, HIV, or kidney failure. The interviews were analyzed utilizing a thematic analysis approach. Results The results suggest that the patient journey of chronically ill patients is a continuous cycle. Furthermore, the results showed that chronically ill patients would like to see digital alternatives for touchpoints implemented into their patient journey. These digital alternatives consisted of video calls, digitally checking in before a physical appointment, digitally self-monitoring one’s medical condition and personally uploading monitoring results into the patient portal, and viewing their own medical status in a digital format. Particularly, patients who were familiar with their healthcare professional(s) and were in a stable condition mostly opted for digital alternatives. Conclusion In the cyclical patient journey, digitalization can help put the wishes and needs of the chronically ill patients at the center of care. It is recommended that healthcare professionals implement digital alternatives for touchpoints. Most chronically ill patients consider digital alternatives to lead to more efficient interactions with their healthcare professionals. Furthermore, digital alternatives support patients to be better informed about the progress of their chronical illness.

The use of digital technologies for extracting information from various data sources can help organizations to reduce uncertainty and improve decision-making. The increasing availability in volume, velocity, and variety of data, however, can give rise to significant risks and challenges in ensuring a high level of information quality (IQ). Pre-digital organizations can be particularly susceptive to such challenges due to their limited experience with digital technologies and IQ governance. We adopt a theory-infused interventionist research approach to assist a pre-digital multinational military organization in navigating its digital transformation (DT) by focusing on IQ. We design and implement an IQ strategy (IQS) by drawing upon organizational information processing theory and examining how the level of IQ can affect the balance between information processing requirements and capacity. We demonstrate that an IQS that incorporates both technological, as well as IQ governance solutions, can support organizations in setting the scope of their DT, decreasing employees’ resistance to change, and increasing their satisfaction, while concurrently improving organizational efficiency. Our work stresses the importance of IQ in the digital era and delineates how pre-digital organizations can navigate DT by strategically addressing IQ.

We consider a retailer who sources her product from a sole supplier. The end market demand is influenced by the quality provided by the supplier. Both supplier and retailer incur costs whenever a low-quality item is sold to the customer. Therefore, both of them have incentive to improve quality. However, the supplier is financially constrained and does not have enough funds to invest in quality. This paper investigates a scenario when the retailer decides to finance the supplier via ‘buyer-direct financing’. In this arrangement, the retailer extends the loan directly to the supplier, and thus accepts the risk of a default. The repayment of the loan is dependent upon the performance of the supplier. We show that there is a unique optimum investment from the retailer which will maximize the retailer’s profit while the supplier is not worse off. We also find the specific level of investment required to reach a pre-defined proportion of damaged units. The study is further exemplified with a numerical.

BackgroundTechnological progress in artificial intelligence has led to the increasing popularity of virtual assistants, i.e., embodied or disembodied conversational agents that allow chatting with a technical system in a natural language. However, only little comprehensive research is conducted about patients' perceptions and possible applications of virtual assistant in healthcare with cancer patients. This research aims to investigate the key acceptance factors and value-adding use cases of a virtual assistant for patients diagnosed with cancer.MethodsQualitative interviews with eight former patients and four doctors of a Dutch radiotherapy institute were conducted to determine what acceptance factors they find most important for a virtual assistant and gain insights into value-adding applications. The unified theory of acceptance and use of technology (UTAUT) was used to structure perceptions and was inductively modified as a result of the interviews. The subsequent research model was triangulated via an online survey with 127 respondents diagnosed with cancer. A structural equation model was used to determine the relevance of acceptance factors. Through a multigroup analysis, differences between sample subgroups were compared.ResultsThe interviews found support for all factors of the UTAUT: performance expectancy, effort expectancy, social influence and facilitating conditions. Additionally, self-efficacy, trust, and resistance to change, were added as an extension of the UTAUT. Former patients found a virtual assistant helpful in receiving information about logistic questions, treatment procedures, side effects, or scheduling appointments. The quantitative study found that the constructs performance expectancy (ß = 0.399), effort expectancy (ß = 0.258), social influence (ß = 0.114), and trust (ß = 0.210) significantly influenced behavioral intention to use a virtual assistant, explaining 80% of its variance. Self-efficacy (ß = 0.792) acts as antecedent of effort expectancy. Facilitating conditions and resistance to change were not found to have a significant relationship with user intention.ConclusionsPerformance and effort expectancy are the leading determinants of virtual assistant acceptance. The latter is dependent on a patient’s self-efficacy. Therefore, including patients during the development and introduction of a VA in cancer treatment is important. The high relevance of trust indicates the need for a reliable, secure service that should be promoted as such. Social influence suggests using doctors in endorsing the VA.

Emerging digital technologies create novel conditions for understanding fundamental societal developments. The academic debate has given little attention to understanding the impact of these digital transformations on key areas such as sustainable development. Hence, this study explores how frugal innovations in the healthcare and energy sector in Bottom of the Pyramid (BoP) markets drive social impact through the use of Internet-of-Things (IoT) technologies. This study focuses on understanding the underlying mechanisms through which technology enabled frugal innovations drive social impact in BoP markets. Using a multiple case analysis approach, the results suggest a distinction between technology providers and enablers as two different types of enterprises working towards developing and commercializing IoT technologies in BoP markets. The findings show that while providers tend to use knowledge on local constrains as inputs to design their activities to achieve local embeddedness, enablers incorporate local constrains in the early technology development process to design customized solutions for local community needs. Findings also highlight that IoT capabilities enable social outcome creation at individual, community and value chain levels. In particular, IoT capabilities moderate the transition from reactive to preventive intervention through their focus on sensing, dynamicity and real-time intelligence.

Aim: To evaluate medical and surgical treatment of postbariatric hypoglycaemia (PBH) in daily practice. Materials and Methods: Retrospective data were extracted from medical records from four hospitals. PBH was defined by neuroglycopenic symptoms together with a documented glucose

PurposeThis study investigates how employees' work- and social-related use of social media can individually and interactively render different impacts on employees' performance in the context of internal or external social media.Design/methodology/approachTo test the research model in these two different contexts, the authors collected data from 392 internal social media users and 302 external social media users in the workplace.FindingsThe data suggest that the respondents' job performance can be enhanced when using internal social media for work-related purposes and using external social media for social-related purposes. Meanwhile, the interaction of work- and social-related use is positive for external social media but negative for internal social media on job performance. These findings highlight the significant distinction of social media use in the workplace.Originality/valueFirst, this study contributes to the literature on the business value of IT by providing theoretical arguments on how companies can capitalize efforts to consider work-related use in combination with social-related use to create business value. Second, this research theorizes two distinct yet interacting views of social media use. The authors offer a more granular insight of the paths from work- and social-related use to employee performance instead of encapsulating social media use in a unitary concept and linking it simply and broadly to employee performance. Third, this research considers the interdependent effects of work- and social-related use on employee performance, and thus goes beyond the independent roles of these two types of social media use. Fourth, the authors find that the links from employees' work- and social-related use of social media to job performance vary in different contexts.

We study the impact of three well-known inventory allocation mechanisms, including proportional, linear, and uniform, on the ordering behavior of retailers serviced from a central distribution center. Based on the allocation mechanism, retailers may have an incentive to adjust (either inflate or deflate) their orders to gain a more favorable allocation, a behavior that may reduce allocation efficiency from a system perspective. We find that while all three mechanisms are centrally optimal under common knowledge of local demands, only the uniform allocation incentivizes retailers to set orders truthfully. Consistent with theory, our experimental results show that using proportional or linear allocation results in larger and more frequent order adjustments, with the degree of strategic ordering being largest under the linear mechanism. Across all mechanisms, order adjustments decrease both allocation efficiency and local retail profits. While uniform allocation results in smaller and less frequent adjustments overall, it may not be feasible to implement in more general settings. Hence, we propose and test a new mechanism, tailored uniform, that leverages the uniform principle while overcoming some practical limitations. It provides more flexibility by allowing for differences in the allocated quantities among retailers, while still providing no incentive for order manipulation. The tailored uniform mechanism performs similarly to uniform in terms of order adjustments, and further increases allocation efficiency when retailers have heterogeneous demands.

PurposeCatastrophic supply chain disruptions can significantly damage the operational and financial performance of firms. While a growing body of literature on supply network structures has studied what influences supply networks' vulnerability to supply chain disruptions and capability to recover from them, it remains unclear how supply network structures change after major supply chain disruptions. We aim to provide an understanding of how these changes occur.Design/methodology/approachUsing a natural experiment approach and supply network data from Factset, this study investigates how firms' supply network structures change after experiencing the catastrophic supply chain disruptions caused by the 2011 Tohoku earthquake and tsunami in Japan. We capture post-earthquake supply network changes using the measures of degree centrality and ego network density.FindingsThe results of the analysis suggest that compared to unaffected firms, the affected firms experience changes in their supply network structures tending toward lower complexity measured by in-degree centrality, out-degree centrality and ego network density.Originality/valueThis study contributes to social network theory and the complex adaptive supply network literature by providing empirical evidence of structural changes in supply networks after catastrophic supply chain disruptions. A managerial contribution is made by providing a reflection on why these changes might be occurring and alert firms to the challenges of managing complexity in their supply networks.

Millions of nanostores around the world face the prospect of digitization, which promises to create significant operational benefits. At the same time, however, digitization may be a risky endeavor. Through the application of a survey and vignette experiments in the field with hundreds of shopkeepers, we explain the perceptions and behavioral processes that shopkeepers incorporate in deciding whether to digitize their operations by adopting smartphone-based technology. We identify two main factors that influence shopkeepers' decision making: Tax Privacy Concerns and Cost. For the first one, given the informal status of nanostores, shopkeepers exhibit privacy concerns for their operational data vis-à-vis the government. Further, we show that the Cost of a technology represents a significant barrier. Both of these features reduce the likelihood that shopkeepers will digitize, thus overshadowing expected productivity gains. Nevertheless, shopkeepers seem willing to digitize, provided technology adds enough value. Finally, we find that both creating positive word of mouth that data are unlikely to be shared with tax authorities and reducing the price of digital technologies help boost digitization.

Smart technologies and increased data availability enable restaurateurs to gather more information about customers and their behavior. These data can be combined with data from other sources to make a wide range of strategic and operational restaurant decisions, and can therefore generate tremendous value for restaurants and their customers. This study focuses on discussing the most promising research opportunities in restaurant operations that leverage data analytics. In particular, we focus on specific research questions across restaurant decision domains such as location, reservation and table management, queue management, menu design and engineering, and multi-channel order management. For each research question, we motivate its practical and theoretical relevance, identify data sources, propose a methodological approach for analysis, and discuss actionable insights for practitioners. As a result, this paper aims to highlight data analytics opportunities for restaurateurs and inspire researchers to contribute in this domain.

In this dialogue paper, we consider Zellweger and Zenger’s (2021) conceptualization of entrepreneurs as scientists, rooted in pragmatism. While we agree that pragmatism provides a useful but neglected foundation for studying the entrepreneurial journey, we maintain that entrepreneurs are more than scientists – in addition, they are engineers, artists, and designers. Our view is predicated on enfolding considerations of time, emergence, and the associated unsurmountable epistemological barrier of unknowability, which enable entrepreneurs to not only describe (predict) the world as scientists do, but also actively shape the future to fit their “mind.”

The increase in stakeholder pressure for responsible business draws closer public scrutiny when buyers use their power advantage illegitimately to exploit weaker suppliers. In this study, we develop the novel concept of buyer abusive behavior (BAB) and examine BABs exerted by buyers of trucking services against truck owner-operators as their suppliers. This focus is timely given the recent emergence of online platform businesses where precarious work and associated worker abuse are prevalent. Building on the theory of power imbalance and risk-taking behavior, we elaborate on how BAB can jeopardize supplier welfare that comprises performance and safety. The analysis of the data pertaining to 260 owner-operators in South Korea shows that contract-unrelated BAB (e.g., buyer's request for money and valuables) harms supplier performance and supplier safety while contract-related BAB (e.g., buyer's unfair subcontract price decision) does not. Furthermore, the positive relationship between supplier performance and supplier safety is attenuated by contract-related BAB but reinforced by contract-unrelated BAB. We contribute to the growing body of the literature on decent work by exposing BAB as a major detriment to supplier worker welfare and laying the groundwork for the development of theories on power abuse and working conditions in multi-tiered subcontracting work environments., Journal of Supply Chain Management, 58 (4), ISSN:1523-2409, ISSN:1745-493X

Operators of major hazard chemical sites increasingly face the problem that their assets are ageing. This paper highlights the major hazard aspects of ageing, particularly in the Netherlands where there are around 400 major hazard chemical sites, many coming to the end of or exceeding their design lifetime. Targeted inspections find failures in the safety management of ageing and every year there are ageing related accidents. Dutch investigated major accidents are analysed in a bow-tie structured database called Storybuilder, which contains 83 major accidents resulting from material degradation, this being 25% of all accidents in the database. The paper provides unique details on the accident causes and the difficulties operators have in foreseeing the outcomes. It explains the reasons for taking a holistic approach to modelling, which considers management, human and technical aspects. The analysis results provide information on the safety barrier, barrier task and barrier management failures. A detailed ageing accident scenario is also illustrated within the holistic model. Two prevention approaches are suggested. One uses scenarios as a basis for identifying the necessary prevention measures. The other results from a Dutch multi-disciplinary maintenance programme concerning smart maintenance, a shared initiative approach of companies looking for innovative solutions. The conclusion is that a scenario-based approach is needed for identifying currently unanticipated material degradation causal events and that, given the condition of ageing assets, a shift to condition-based maintenance, combined with technical, organisational and cultural changes, underpins the future approach to physical ageing.