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The nature and amount of data that public organizations have to monitor to counteract corruption lead to a phenomenon called “KPI overload”, consisting of the business analyst feeling overwhelmed by the amount of information and resulting in the absence of appropriate control. The purpose of this study is to develop a solution based on Artificial Intelligence technology to avoid data overloading and, at the same time, under-controlling in business process monitoring.

The authors adopted a design science research approach. The authors started by observing a specific problem in a real context (a healthcare organization); then conceptualized, designed and implemented a solution to the problem with the goal to develop knowledge that can be used to design solutions for similar problems. The proposed solution for business process monitoring integrates databases and self-service business intelligence for outlier detection and artificial intelligence for classification analysis.

The authors found the solution powerful to solve problems related to KPI overload in process monitoring. In the specific case study, the authors found that the combination of Business Intelligence and Artificial Intelligence can provide a significant contribution to the detection of fraud, corruption and/or policy misalignment in public organizations.

The authors provide a big-data-based solution to the problem of data overload in business process monitoring that does not sacrifice any monitored Key Performance Indicators and that also reduces the workload of the business analyst. The authors also developed and implemented this automated solution in a context where data sensitivity and privacy are critical issues.

In the healthcare management domain, there is a lack of knowledge concerning the role of resilience practices in improving patient safety. The purpose of this paper is to understand the capabilities that enable healthcare resilience and how digital technologies can support these capabilities.

Within- and cross-case research methodology was used to study resilience mechanisms and capabilities in healthcare and to understand how digital health technologies impact healthcare resilience. The authors analyze data from two Italian hospitals through the lens of the operational failure literature and anchor the findings to the theory of dynamic capabilities.

Five different dynamic capabilities emerged as crucial for managing operational failure. Furthermore, in relation to these capabilities, medical, organizational and patient-related knowledge surfaced as major enablers. Finally, the findings allowed the authors to better explain the role of knowledge in healthcare resilience and how digital technologies boost this role.

When trying to promote a culture of patient safety, the research suggests healthcare managers should focus on promoting and enhancing resilience capabilities. Furthermore, when evaluating the role of digital technologies, healthcare managers should consider their importance in enabling these dynamic capabilities.

Although operations management (OM) research points to resilience as a crucial behavior in the supply chain, this is the first research that investigates the concept of resilience in healthcare systems from an OM perspective, with only a few authors having studied similar concepts, such as “workaround” practices.

This study formulates a new archetypical model that describes and re-interprets the patient–physician relationship from the perspective of two widespread phenomena in the healthcare delivery process: value co-creation (VCC) and defensive medicine (DM).

Grounded in the existing literature on VCC and DM, the authors designed and conducted 20 in-depth interviews with doctors (and patients) about their past relationships with patients (and doctors). After putting the recorded interviews through qualitative analysis with a three-level coding activity, the authors built an empirically informed model to classify patient–physician relationships.

The authors identified four archetypes of patient–physician relationships. Each archetype is described along with its representing characteristics and explained in terms of its consequences as they relate to VCC and DM.

This research contributes to the literature on both VCC in healthcare and DM, in addition to the patient–physician's relationship literature.

Being aware of patient–physician relationship mechanics, building long-term relations with patients and investing in service personalization and patient-centred care can effectively mitigate the risks of DM behaviours on one side while increasing the likelihood of VCC actualization on the other.

Although strictly linked to the interactions between patients and doctors, VCC and DM are typically considered disentangled. In this research paper, the authors identified four archetypes of patient–physician relationships in relation to these two phenomena.

The study focuses on the value co-creation processes in humanitarian professional services provision, analysing the key enabling factors of beneficiaries' participation, involved in long-term integration programmes (L-TIPs).

Through an in-depth case study, the research looks at the practices of value co-creation in humanitarian professional services, considering both the perspectives of the professional service provider and beneficiary.

In professional services beneficiary's participation affects the success of the L-TIPs outcomes. Participation's enablers can be classified into four different spheres, each belonging to different elements of professional service: the beneficiary, the professionals, the service design and the external environment.

This paper contributes to the literature on humanitarian operations & supply chain management. By focussing on an understudied phase of the disaster life-cycle management, it contributes to the theory of value co-creation by exploring new issues and drivers of beneficiary's participation.

This research has interesting implications for policymakers and humanitarian practitioners. First, guidelines for professionals' behaviours and interventions should be designed as well as new practices and strategies should be adopted. Second, governments should avoid concentrating L-TIPs in few big humanitarian centres.

The study focuses on an understudied stage of humanitarian operations, namely the L-TIPs, and uses this setting to build on the theory of value co-creation in professional services by identifying its enabling factors, clustered into four spheres, namely beneficiary, professional, service design and environmental.

The purpose of this paper is to explore the effect of inventory record inaccuracy due to behavioral aspects of workers on the order and inventory variance amplification.

The authors adopt a continuous-time analytical approach to describe the effect of inbound throughput on the inventory and order variance amplification due to the workload pressure and arousal of workers. The model is numerically solved through simulation and results are analyzed with statistical general linear model.

Inventory management policies that usually dampen variance amplification are not effective when inaccuracy is generated due to workers’ behavioral aspects. Specifically, the psychological sensitivity and stability of workers to deal with a given range of operational conditions have a combined and multiplying effect over the amplification of order and inventory variance generated by her/his errors.

The main limitation of the research is that the authors model workers’ behavior by inheriting a well-known theory from psychology that assumes a U-shaped relationship between stress and errors. The authors do not validate this relationship in the specific context of inventory operations.

The paper gives suggestions for managers who are responsible for designing order and inventory policies on how to take into account workers’ behavioral reaction to work pressure.

The logistics management literature does not lack of research works on behavioral decision-making causes of order and inventory variance amplification. Contrarily, this paper investigates a new kind of behavioral issue, namely, the impact of psycho-behavioral aspects of workers on variance amplification.

The purpose of this paper is to analyse the impact of reverse logistics on order and inventory variance amplification in a single-echelon supply chain (SC) and to propose a new order policy for dampening such amplification.

A general review of the literature on sustainable operations and on the impact of reverse logistics on SC performance provides the foundation for the study. The authors use difference equation math approach for modelling and analysing a closed SC. A proper design of experiment and data collected from the European Union statistics validate the obtained numerical results.

The variability of reverse flow in a closed loop SC increases the serviceable inventory variance. However, a proper design of the reverse flow considerably improves the global performance. To this purpose, the authors propose a new order policy, namely R-APIOBPCS, which explicitly considers the reverse flow of products.

The paper presents a math model describing a closed loop supply chain (CLSC). No empirical analysis is provided. Future researches should evaluate the impact of the proposed R-APIOBPCS on more realistic closed loop SC models.

The paper ' s findings may motivate logistics and SC managers to implement CLSC when supported by innovative, suitable tools for the proper management of the information and material flow in the chain. Managers should be well acquainted that, by doing so, they not only satisfy national and international legislations but also achieve improvements in logistics performance.

The authors propose a novel replenishment rule that accurately coordinates the upstream and downstream flows in a SC. The proposed order policy can be reasonably considered one of the advocated managerial tools for the proper management of reverse logistics: it allows reducing inventory and limiting the variability of the orders placed to suppliers in SC with reverse logistics.

Many research studies in operations management (OM) and strategic management (SM) investigate how different kinds of firm decisions regarding business relationships can positively affect a firm's operations performance, resource endowment, and competitive position. Very few studies exist, however, that have attempted to illuminate the actual behaviors of managers when making strategic decisions about their intercompany relationships; rather, most existing studies focus on normative theory. The purpose of this paper is to explore linkages between the “set” of strategic objectives that managers are willing to pursue, the “set” of networking decisions they make, and the “set” of business agreements they sign.

In order to investigate and explore actual managerial behaviors with respect to networking strategy, the study adopts a field research approach based on multiple case studies. Data were collected on 13 business agreements from three manufacturing firms in the mechatronics industry in Italy. Within‐case and cross‐case analyses are used for theory‐building purposes.

The empirical data allow identification four different archetypes of networking strategy. The archetypes capture different connections between the “set” of strategic objectives that managers are willing to pursue, the “set” of networking decisions that they consider, and the “set” of strategic agreements that they actually adopt. Specifically, the identified archetypes are named multi‐alignment, multi‐agreement (diversification), multi‐objective, and mono‐alignment (focus), and these are related to different association multiplicities among objectives, decisions, and agreements. The implications related to these archetypes are three‐fold. First, the multi‐alignment archetype suggests a focus not just on one kind of agreement, but also on the firm's overall portfolio of agreements, in order to facilitate understanding of how different kinds of agreements and networking decisions can play a complementary role in achieving a firm's predetermined business objective/s. Second, the multi‐agreement (diversification) archetype suggests that managers can minimize the risk of losing the potentiality of network collaboration by undertaking different kinds of agreements for the same strategic objective. Third, the mono‐alignment (focus) and multi‐objective archetypes suggest that just one agreement can potentially pursue one or multiple strategic objectives, and thus can allow managers to minimize the cost of managing several networking relationships.

The originality of this study lies in its exploration of linkages between objectives, decisions and networking agreements. Unlike most of the existing papers in OM and SM, however, it does not specifically focus on: vertical or horizontal relationships; operations performance (positioning school) or resource endowment (resource‐based view) strategic objectives; or any specific kind of agreement contract (outsourcing, alliance, joint venture, etc.). This paper presents four different networking strategy archetypes that represent different ways of matching a “set” of networking decisions, strategic objectives and business agreements. These are not related to either vertical or horizontal relationships, operations performance or resource endowment objectives, or any specific contract agreement form.