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Diffusion of innovations, defined as the adoption and implementation of new ideas, processes, products, or services in health care, is both particularly important and especially challenging. One known problem with adoption and implementation of new technologies is that, while organizations often make innovations immediately available, organizational actors are more wary about adopting new technologies because these may impact not only patients and practices but also reimbursement. As a result, innovations may remain underutilized, and organizations may miss opportunities to improve and advance. As innovation adoption is vital to achieving success and remaining competitive, it is important to measure and understand factors that impact innovation diffusion. Building on a survey of a national sample of 654 clinicians, our study measures the extent of diffusion of value-enhancing care delivery innovations (i.e., technologies that not only improve quality of care but has potential to reduce care cost by diminishing waste, Faems et al., 2010) for 13 clinical specialties and identifies healthcare-specific individual characteristics such as: professional purview, supervisory responsibility, financial incentive, and clinical tenure associated with innovation diffusion. We also examine the association of innovation diffusion with perceived value of one type of care delivery innovation – artificial intelligence (AI) – for assisting clinicians in their clinical work. Responses indicate that less than two-thirds of clinicians were knowledgeable about and aware of relevant value-enhancing care delivery innovations. Clinicians with broader professional purview, more supervisory responsibility, and stronger financial incentives had higher innovation diffusion scores, indicating greater knowledge and awareness of value-enhancing, care delivery innovations. Higher levels of knowledge of the innovations and awareness of their implementation were associated with higher perceptions of the value of AI-based technology. Our study contributes to our knowledge of diffusion of innovation in healthcare delivery and highlights potential mechanisms for speeding innovation diffusion.

This study aims to analyze the effects of interorganizational cost management and opportunism on the reflexes of relational norms on satisfaction with interorganizational cooperation in franchised companies. The collective synergy arising from these relationships mainly seeks to increase competitiveness and commercial development. Windolph and Moeller observed that interorganizational cost management increases satisfaction in the relationship with partners, while relational norms attenuate the negative effect on supplier satisfaction.

A survey was carried out with managers of franchised companies in the food industry. The managers were identified on the social network Linkedin. After that, an invitation was sent to participate in the research. A total of 88 valid responses were obtained. The questionnaire consists of 40 extracted assertions. A pre-test was carried out to verify the comprehensibility of the wording of the assertions. Structural equation modeling with partial least squares (PLS-SEM) was used for data analysis. For analysis, validation and adequacy tests of the model were carried out, and executed in the software SmartPLS.

Survey results reveal that interorganizational cost management increases franchisor relationship satisfaction. Relational social norms mitigate the negative effect of opportunism on satisfaction with cooperation. And interorganizational cost management plays an important role in the relationship between relational norms and satisfaction with cooperation between franchisor and franchisees.

However, limitations resulting from the methodological design of the research must be considered in the interpretation of the results, at the same time that they provide opportunities for new research. As for the methodological aspects, the study cannot be generalized to other branches of companies, because it is a sector with franchises with specific characteristics. It should also be considered that the study was limited to investigating the proposed model, but other constructs can be observed in the literature. Finally, to empirically assess the constructs of the theoretical model, research instruments from studies other than those considered here can be used.

This study contributes with relevant literature and the management practice of interorganizational cooperation by empirically demonstrating the importance of interorganizational cost management as a management control mechanism and to mitigate the effects of opportunism between franchisor and franchisees.

It also contributes to the inclusion of social norms in the relationship between franchisor and franchisees with a view to increasing franchisee satisfaction with their franchisor, which also aims to mitigate the impacts of opportunism in this relationship. It contributes to the social order, as they reveal ways to mitigate possible conflicts between franchisor and franchisee and generate greater transparency in the relationship.

This study is justified by the fact that it investigates relational aspects of cooperation between franchisor and franchisees, a form of interorganizational cooperation that is growing in the market. It is also justified by highlighting the importance of interorganizational cost management as a means of mitigating the opportunistic effects between franchisor and franchisees, proving to be an important management mechanism. Research is especially important because interorganizational strategies have been spreading in corporate environments (Dekker, Ding & Groot, 2016) and the maintenance of the relationship is dependent on satisfaction with cooperation.

This study furthers one’s understanding of the motivations of the crowdfunding crowd by empirically examining critical factors that influence the crowd's decision to support a crowdfunding project.

Backer's comments from a sample of the top 100 most funded technology product projects on KickStarter were collected. A latent Dirichlet allocation (LDA) analysis strategy was adopted to investigate critical motivational factors. Three experts mapped those factors to the known theoretical constructs of social exchange theory (SET).

Although backers are motivated by value, they are also motivated by far less tangible social factors including trust and a feeling of psychological ownership. Findings suggest that the crowd is far more than a passive group of investors or customers and should be viewed as participatory stakeholders. This study serves as guidance for project owners hoping to motivate the crowd and for future investigators examining backer motivations in other types of crowdsourcing projects.

Online chatter in the form of user-generated comments is an excellent data source for researchers to mine for value and meaning.

Given strong feelings of psychological ownership, project owners should actively engage the crowd and solicit the crowd for advice and help in order to motivate them.

The study presents the first empirical exploration of backer motivations using LDA guided by theory and the knowledge of experts. A framework of latent motivational factors is proposed.

Human fascination in the unidentified flying objects (UFOs) and alien paranormal phenomenon is rich in history, explored widely in popular culture and many personal beliefs exist across society. The tourism industry offers a range of places where consumers can encounter such a phenomenon. Reports continue to highlight the growth in consumers participating at UFO and alien tourism attractions and locations. Significantly, the purpose of this paper is to shine a light on the relationship between UFOs, aliens and the tourism industry.

This paper takes a pragmatic philosophical approach by embracing a multi-disciplinary analysis. This study examines a range of secondary data information, statistics, reports and research studies.

By identifying the current impotence of the UFO and alien tourism markets and the growing consumer participation in it, this paper presents a theoretical starting point in the form of a model, which maps the current landscape of the industry from supply and demand perspectives. This study should be seen as a stepping stone towards further research into the UFO and alien tourism industry and provide researchers with a theoretical platform and novel ideas through which to explore the subject.

The phenomenon includes an established eclectic mix of attractions and likewise tourist motivations for visiting are wide and diverse. However, the subject lacks academic consideration. Thus, this paper presents original research and timely discussions on the topic.

The purpose of this paper is to examine millennial customer perceptions of food trucks and to identify factors that can foster their behavioral intentions pertaining to food trucks.

The study is based on a sample of 247 millennial customers of various food truck vendors in the United States and was assessed using ordinary least squares regression analysis.

Food truck image and employee friendliness were found to impact both customer satisfaction and word of mouth behavior; however, the other hypotheses were not supported.

There were two limitations. The first was that one of the constructs did not achieve the minimum average variance extracted. The second was that data collection was done in a single city in the United States; therefore, future research could overcome these limitations through a refinement of the construct’s items and targeting more cities.

There has been limited academic research on the millennial customer perceptions of the food truck phenomenon. This research addresses that gap through a field study that examines factors that contributed to the growth and popularity of food trucks among millennials

As corporate sustainability is systemic, it cannot be achieved without effective involvement of suppliers. This study aims to examine the drivers of supplier companies’ resource allocation to a sustainability issue that affects customer companies and society at large.

Supplier companies’ resource allocation for a sustainability issue is explained from variables at the levels of the institutional, supply chain and internal environments of a supplier company. The framework is tested with a moderated regression model on 102 supplier companies in animal-based supply chains, focussing on their resource allocation for farm animal welfare.

The findings show that supply chain factors have the strongest influence on suppliers’ resource allocation, including a strong effect of investment specificity and a U-shaped effect of chain integration. Also, significant effects from institutional variables, namely, the pressure on consumer companies, and an inverted U-shaped effect of sustainability competition are found. The innovativeness, referring to the internal environment of supplier companies, appears as another important factor for the allocation of resources to animal welfare, as a sustainability issue.

The results have implications for consumer market companies to deal with sustainability issues that require involvement of their suppliers, for supplier companies to increase their competitive positions and strengthen their relationships within the supply chain, and for policymakers seeking solutions for sustainability issues in the market domain.

While existing literature focusses mostly on the corporate sustainability of highly visible and large consumer companies, to the best of the authors’ knowledge, this study is the first to examine the drivers of supplier companies’ resource allocation for a sustainability issue, namely, animal welfare. It provides insights on what drives supplier companies, usually operating outside the spotlight, to become part of a sustainability transition.

The purpose of this paper is to apply the conjugate gradient (CG) method, together with the adjoint operator (AO) to the pulsating heat pipe problem, including some quite interesting experimental results. The CG method, together with the AO, was able to estimate the unknown functions more efficiently than the other techniques presented in this paper. The estimation of local heat transfer coefficients, rather than the global ones, in pulsating heat pipes is a relatively new subject and presenting a robust, efficient and self-regularized inverse tool to estimate it, supported also by some experimental results, is the main purpose of this paper. To also increase the visibility and the general use of the paper to the heat transfer community, the authors include, as supplemental material, all numerical and experimental data used in this paper.

The approach was established on the solution of the inverse heat conduction problem in the wall by using as starting data the temperature measurements on the outer surface. The procedure is based on the CG method with AO. The here proposed approach was first verified adopting synthetic data and then it was validated with real cases regarding pulsating heat pipes.

An original fast methodology to estimate local convective heat flux is proposed. The procedure has been validated both numerically and experimentally. The procedure has been compared to other classical methods presenting some peculiar benefits.

The approach is suitable for pulsating heat pipes performance evaluation because these devices present a local heat flux distribution characterized by an important variation both in time and in space as a result of the complex flow patterns that are generated in this type of devices.

The procedure here proposed shows these benefits: it affords a general model of the heat conduction problem that is effortlessly customized for the particular case, it can be applied also to large datasets and it presents reduced computational expense.

In 1951, Kenneth Arrow proved that it is not possible to have a group decision-making procedure that satisfies reasonable requirements like fairness. From the theoretical viewpoint, this is a great result – well-deserving the Nobel Prize that was awarded to Professor Arrow. However, from the practical viewpoint, the question remains – so how should we make group decisions? A usual way to solve this problem is to provide some reasonable heuristic ideas, but the problem is that different seemingly reasonable idea often lead to different group decision – this is known, e.g. for different voting schemes.

In this paper we analyze this problem from the viewpoint of decision theory, the basic theory underlying all our activities – including economic ones.

We show how from the first-principles decision theory, we can extract explicit recommendations for group decision making.

Most of the resulting recommendations have been proposed earlier. The main novelty of this paper is that it provides a unified coherent narrative that leads from the fundamental first principles to practical recommendations.