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This study aims to evaluate how stakeholders affect project risks by analyzing the connection between stakeholder management and risk management in the information technology (IT) project context.

Using the Delphi method, interviews with IT project experts were conducted to examine four factors concerning stakeholder management and define probabilities for three risk variables. The design of experiments (DoE) method was applied for the design of the research instrument and data analysis.

Stakeholder engagement and communication with stakeholders have significant influence on the occurrence of negative risks, opportunities and the development of contingency strategies. These results provide project leaders with relevant data that better guide actions toward stakeholders and enhance project success probability.

This study clarifies important aspects of two main project management areas – stakeholder and risk management – in the IT projects context. This research also presented an unusual application for the DoE method which allows the subjective variables analysis by statistical tools and enables to explore factor influences on real project situations.

The evolution of e-health technologies presents promising alternatives for health-care excellence. Despite the benefits arising from mobile e-health (m-health) and wearables technologies, the literature stands many contradictories signs regarding how users accept and engage in using these technologies. This study aims to synthesize the estimations about m-health user acceptance technologies.

A meta-analytic structural equation modeling was carried out using the 778 relationships estimated by 100 previous research. The estimations follow the relations and constructs proposed in the UTAUT2 technological acceptance model.

The results indicate the performance expectancy, effort expectancy, social influence and habit constructs are most important for predicting the behavioral intention of use of m-health technologies. The Latin American users of e-health technologies are still underestimated in the literature.

The study presents a guide to understanding the acceptance process of m-health technologies and delivers a general orientation for developing new m-health devices considering their acceptance by users.

This study is to propose a procedure to support decisions on which enablers should be employed to minimize the impact of barriers to implementing mass customization strategies in food companies.

Through interpretive structural modeling, the authors analyzed the relationships between barriers. Then, with an approach similar to the quality function deployment technique, commonly used in general product and process development, the authors clarified the relationships between barriers and enablers.

The results revealed 19 barriers and 17 enablers for implementing food mass customization. The analysis indicates that most of the barriers (16) present strong associations with each other. The barrier “products with non-customizable features” depends on the whole chain of associations and causes a minor impact on the other barriers. In turn, the barrier “ingredient incompatibility” causes impact over the whole chain, and its dependence on other barriers is very low.

The results were tested in a single Brazilian company in the food sector.

The findings can allow food manufacturing companies to focus their efforts on the improvement of enabling technologies, such as smart packaging, Internet of Things and additive manufacture.

This study would help food companies to improve their business and provide better products to society.

There are few recommendations in the literature to how to implement mass customization strategy in companies from the food sector. This study fills in this gap presenting a procedure to guide managerial staff to develop this promising approach for food companies.

The purpose of this paper is to examine the relation between the utilization of the customization strategy and the availability of the online toolkit and its features with the commercial variables of businesses.

The sample used in this paper consists of 134 cases of corporate brands in the automobile industry; their sales correspond to 49.12 percent of vehicles produced in 2012. The logistic regression analysis was then applied to the sample.

This paper confirmed the relationship between the use of toolkits for customization and business variables, like vehicle sales.

The generated model allows the prediction of market conditions which recommended to provide the toolkit for customization, and if implemented, what combination of features it must have.

Previous studies have identified a variety of Internet of Things (IoT) business models and have recognised the complexity related to the application of IoT technologies in business, along with the potential of the modularity concept application in organisational design. The purpose of this paper is to identify the main building blocks for the development of a business model canvas for companies that adopt the IoT in their business.

First, the authors carried a systematic literature review to identify theoretical, experimental and practical IoT business model canvas recorded in the literature. Then, the authors identified and analysed the characteristics of the building blocks present in these canvas using a statistical cluster technique. Based on the outcomes, the authors proposed a framework with standard and optional modules to allow flexible arrangements and suit different IoT business goals.

The results revealed that the IoT business model canvas recorded in the literature had been grossly designed to attend two drivers: manufacture and service organisations. Therefore, based on the frequency of building blocks present in IoT business model canvas recorded in the literature, it has been proposed two flexible frameworks which can be tailored to accommodate the immense variety of possibilities offered by IoT technologies in manufacture and service business.

The business model frameworks proposed in this research can support entrepreneurs structuring new IoT businesses or upgrading existing businesses.

This research offers a comprehensive IoT business model framework with their respective building blocks built from an extensive literature review.

This article aims to compare smart meters' acceptance studies worldwide to consolidate trends and highlight factors that are not a consensus.

This work performs a statistical meta-analysis, using the Hunter–Schmidt method and the UTAUT2 model, of the factors of acceptance of smart meters in the world literature. A meta-regression was also conducted to verify the moderation exercised by gender, level of education and timeline context of the articles.

The main results point to hedonic motivation, performance expectancy and effort expectancy as the leading influencers for smart meter's acceptance. Meta-regression indicates that the influence is more significant among the male gender and that over the years, the social influence must gain weight in the smart meter's acceptance.

Specific strategies are suggested to improve projects for the implementation of smart meters based on the obtained results.

The contribution given by this work is relevant, considering it is the first meta-analysis focused on smart meters' acceptance published in the literature

The purpose of this paper is to understand how the association between leadership styles (task or relation orientation) and lean manufacturing (LM) implementation changes due to two contextual variables, team size and the leader’s age.

The authors carried out a survey with 225 leaders from different Brazilian companies that are implementing LM. Research constructs were validated through rigorous procedures using confirmatory factor analysis. Hypotheses were tested using ordinary linear least squares regression.

The results suggest that larger teams and more senior managers were negatively associated with LM implementation. Task-orientation style makes leaders more likely to achieve higher levels of LM than relation-orientation style leaders. Finally, the influence of relation-oriented leaders on LM implementation is contingent upon the size of the team.

Regarding study’s limitations, sample size and respondents’ location restrict results to this contextual condition, indicating that increasing the sample would help provide wider and more generalizable results. It is also worth noting that results are based on respondents’ (leaders) perspective. Hence, future studies may collect data from multiple perspectives, such as leaders and their followers, in order to compare results so as to verify the convergence or divergence among different respondents.

The results suggest that leaders should have different behaviors according to the context in which they are inserted. Therefore, such behavioral prescriptions are useful for managers since they are pressured to achieve high operational performance in short time periods and with few resources. Further, companies undergoing lean implementation may also be able to stimulate proper leadership behaviors and promote development programs accordingly, which is extremely relevant since behavioral changes usually take time.

The evolutionary process for achieving a successful lean enterprise requires different leadership styles according to the context in which leaders are inserted. This research provides arguments to help better understand the recommended leadership behaviors for lean implementation, complementing existing roadmaps by considering the proper leadership style as a contingency issue during lean implementation. Moreover, identifying the effect of contextual variables helps specify the contexts in which lean practices are more likely to be implemented.

The purpose of this paper is to propose an instrument for assessing the relationships between the critical success factors (CSFs) that promote help chain, providing means to enhance overall equipment effectiveness (OEE) and quality performance in companies undergoing a lean implementation.

The aforementioned relationships were determined and validated through a survey carried out with 50 Brazilian manufacturers. The authors, thus, provide an empirically validated instrument for assessing help chain CSFs and their impact on key operational performance indicators with no parallel in the existing literature. Quality (incidence of scrap and rework in manufacturing processes) and OEE (overall equipment effectiveness measured in percentage) were chosen as performance indicators because of their recognized relevance in previous research related to help chain approach.

The results of this paper show that the size of the company and CSFs have a significant relationship with quality. However, for OEE, time of lean implementation seems to be significantly important to predict its performance.

Identifying relevant relationships between CSFs and performance indicators may contribute to specify the context in which problems are expected to occur. With that knowledge, manufacturers will be able to emphasize the development of such factors that tend to improve their operational performance. Therefore, possible correlations are investigated to obtain a clearer comprehension around the subject and enable a better understating over the boundary conditions that surround the problem.

While previous operations management literature acknowledges the positive influence of Lean and Industry (I4.0) on performance, recent studies examining the synergy between these two factors have produced inconsistent and contradictory results. Therefore, this study aims to provide a comprehensive understanding of the effect of Lean and I4.0 synergy on firm performance.

This study utilised a meta-analysis approach, examining 23 empirical studies exploring multiple effects of the Lean and I4.0 synergy on firm performance. Multiple subgroup analyses were conducted to assess the contradictory outcomes and identify in what conditions such synergy may achieve performance.

The results affirm the prevailing positivist perspective among most scholars regarding the positive influence of the Lean and I4.0 synergy on firm performance. However, the overall effect size derived from the studies indicates a weak relationship, suggesting that this synergy alone is not the sole determinant factor of firm performance. In addition, the subgroup analyses reveal the presence of contingent conditions that may affect the performance outcomes when integrating Lean and I4.0, as most effects exhibit a weak relationship.

This study represents the first meta-analysis investigating the relationship between the Lean and I4.0 synergy on firm performance. By shedding light on the contradictory effects often depicted in the operations management literature, this study provides a critical reflection for researchers who tend to adopt an overly optimistic view of such synergy.

The purpose of this paper is to empirically investigate the relationships among the implementation of LSC practices. Particularly, the authors examine the adoption level of 27 LSC practices, which were identified in a literature review, within 113 manufacturing companies from different sectors located in Southern Brazil.

Data collected were analyzed by means of multivariate techniques (partial correlation analysis) and two control variables were used: level of onshore suppliers and company’s experience on lean manufacturing implementation.

The results showed that the relationship among practices may not always be synergic, since there are pairs of practices that, when concurrently implemented they tend to conflict, hindering their benefits.

The use of partial correlations between pairs of LSC practices provides means to better understand specific associations, disregarding the implementation effect of the whole set of practices. The research also provides managers and practitioners arguments to better comprehend how practices interact with each other under specific contexts.