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The purpose of this paper is to explore how organizations manage and integrate exploration and exploitation across the innovation project portfolio. Such ambidextrous capabilities are required for organizations to innovate and succeed in today's rapidly changing competitive environment. Understanding how exploration and exploitation projects are integrated can illustrate ways to enhance ambidexterity and boost learning for the benefit of both approaches.

A multiple-case study approach was used to explore innovation portfolio management in six large organizations that emphasize innovation in their strategies.

The findings draw upon concepts of paradox and contingency to reveal that the inherent tension between formality and flexibility in managing innovation project portfolios is aligned with the need for organizational ambidexterity that maintains effective exploitative innovation while supporting explorative innovation capabilities. Four integration mechanisms are identified that enhance ambidexterity across the innovation portfolio by embedding processes for transition from exploration to exploitation and cross-fertilizing knowledge to build innovation capability across both exploration and exploitation.

Managers may find inspiration on ways to enhance learning by bridging exploration and exploitation projects from the four types of integration mechanisms. Recognizing the paradoxical nature of the tension between formality and flexibility in project and portfolio management may also help guide organizations to effectively develop ambidextrous approaches to enhance overall innovation outcomes.

In contrast to perspectives which suggest that paradox and contingency approaches represent disparate perspectives, the authors demonstrate how they can complement each other and work together through innovation portfolio management to support ambidexterity at the portfolio and project levels.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Firms can optimize innovation outcomes by creating portfolios containing both exploitation and exploration projects. Development of ambidexterity capabilities helps attainment of such aims as companies will be more able to manage the inherent paradoxes of an integrated portfolio and the need to balance formality and flexibility in the approach.

The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

The present work has proposed and employed an innovative hybrid method based on the combination of factor analysis and an artificial neural network (ANN) model to forecast customer satisfaction from the identified dimensions of service quality in India, a developing country.

The qualitative study is conducted with Internet banking users to understand e-banking clients' perceptions. The data is collected with the help of a questionnaire from randomly selected 208 customers in India. Firstly, factor analysis was performed to determine the influential factors of customer satisfaction, and four factors i.e. efficiency, reliability, security and privacy, and issue and problem handling were extracted accordingly. The neural network model is then applied to the factor scores to validate the key elements. Lastly, the comparative analysis of the actual ANN and the regression predicted result is done.

The success ability of the linear regression model is challenged when approximated to nonlinear problems such as customer satisfaction. It is concluded that the ANN model is a better fit than the linear regression model, and it can recognise the complex connections between the exogenous and endogenous variables. The results also show that reliability, security and privacy are the most influencing factors; however, problem handling and efficiency have the slightest effect on bank client satisfaction.

This research is conducted in India, and the sample is chosen from the urban area. The limitation of the purposeful sampling technique and the cross-sectional nature of the data may hamper the generalisation of the results.

The conclusions from the study will be helpful for policymakers, bankers and academicians. To our knowledge, few studies used ANN modelling to predict customer satisfaction in the service sector

Consumers worldwide are increasingly adopting mobile payments. However, despite its global popularity, this innovation did not diffuse among American consumers extensively. As of 2019, less than 30% of smartphone users in the USA engaged in mobile payments. The purpose of this paper is to investigate drivers of mobile payment adoption in the USA and to explore the mediating factors of consumers’ attitudes toward mobile payments.

Data were collected through Amazon M-Turk in the USA with 222 final respondents. Participants received an incentive to participate in this study. The measurement and structural models were evaluated by the component-based partial least squares (PLS) approach using Smart-PLS 3 software.

The study shows several factors affecting consumers’ attitudes toward mobile payments. Specifically, relative advantage, compatibility, observability, perceived security and convenience influence attitudes toward mobile payments and, consequently, behavioral intent to use mobile payment technology. This investigation contributes to the ongoing inquiry on the adoption of mobile payment technology in the USA. It offers specific insights for managers on how to increase mobile payment adoption. The study establishes a modified diffusion of innovations (DOI) model of consumer attitudes toward the use of mobile payments.

The objective of this study is to focus mainly on consumers in the USA, and it limits the generalizability of this study.

This study contributes to the current research on mobile payment adoption. Based on theoretical considerations, the authors derived a research model specifying critical drivers of an individual’s intentions to use mobile payments. Specifically, we establish a modified DOI-based model of consumer attitudes towards mobile payments. It shows several contributing factors affecting consumers’ attitudes toward mobile payments. The paper has important managerial implications aimed at the increase of the diffusion of mobile payments in the USA.

M-wallets have emerged as one of the most important financial innovations of the 21st century, enabling users to carry digital cash by securely storing payment methods on their mobile devices. However, the continued use of m-wallets varies among people for several reasons. This study used the technology continuation theory (TCT), gamification and trust factors to examine the variables affecting consumers' intentions to continue using mobile wallets.

The SmartPLS partial least squares software was used to analyze data from 431 m-wallet users in Vietnam using the structural equation modeling technique.

The data revealed that the research model can predict users' intentions to continue using mobile wallets. TCT constructs demonstrated strong exploratory power in explaining consumer satisfaction and attitudes towards m-wallets. Furthermore, the study confirmed the direct effect of the perceived effectiveness of gamification on perceived ease of use and attitude, as well as its indirect effect on consumers' continued use intentions of mobile wallets via attitude. In addition, the trust negatively influenced consumers' intentions to continue using m-wallets.

The findings of this study can help researchers, practitioners and policymakers improve m-wallet design, development and adoption, as well as advance financial technology and define the future of digital payments in terms of consumer attraction, engagement and financial inclusion.

Based on TCT theory, this study enriches m-wallet research by examining two important factors, gamification and trust, and thus provides insights into how to improve consumers’ intentions to continue using m-wallets in developing countries. This study offers timely insights into theory and practice regarding these factors. It therefore paves the way for researchers and practitioners to learn how easy, enjoyable and secure the end-user experience should be to keep users engaged with m-wallets.

This paper aims to investigate the evolution, roots and influence of the rural entrepreneurship literature.

Using a bibliometric exercise, the analysis starts with investigation of studies on entrepreneurship and gathering all (772) articles on rural entrepreneurship (from 1981 to 2020) found in both Scopus and Web of Science up to 15 August 2020. Citation analysis of the references/citations of 755 articles are listed in the abstract database, generating a citation database involving 46,432 references/citations. This paper considers 635 (out of the 772) articles on rural entrepreneurship (i.e. articles cited in one or more studies), generating a database of 10,767 studies influenced by the rural entrepreneurship literature.

This study discovers that the relative importance of rural entrepreneurship within the entrepreneurship literature has increased in the last few years, but rural entrepreneurship remains a European concern; the most frequently addressed topics include growth and development, institutional frameworks and governance and rurality, with theory building being rather understudied. Most of the studies on rural entrepreneurship are empirical, involving mainly qualitative analyses and targeting high income countries; rural entrepreneurship is rooted in the fields of economics and entrepreneurship and is relatively self-referential.

This study provides a comprehensive and updated investigation of evolution of the rural entrepreneurship literature. The assessment of the literature’s scientific roots of rural entrepreneurship had not yet been tackled before. To the best of the author’s knowledge this study can be considered as the first effort for identifying the scientific influence of the rural entrepreneurship literature.

External stakeholder risks (ESRs) caused by unfavorable behaviors hinder the success of project portfolios (PPs). However, due to complex project dependency and numerous risk causality in PPs, assessing ESRs is difficult. This research aims to solve this problem by developing an ESR-PP two-layer fuzzy Bayesian network (FBN) model.

A two-layer FBN model for evaluating ESRs with risk causality and project dependency is proposed. The directed acyclic graph (DAG) of an ESR-PP network is first constructed, and the conditional probability tables (CPTs) of the two-layer network are further presented. Next, based on the fuzzy Bayesian network, key variables and the impact of ESRs are assessed and analyzed by using GeNIe2.3. Finally, a numerical example is used to demonstrate and verify the application of the proposed model.

The proposed model is a useable and effective approach for ESR assessment while considering risk causality and project dependency in PPs. The impact of ESRs on PP can be calculated to determine whether to control risk, and the most critical and heavily contributing risks and project(s) in the developed model are identified based on this.

This study extends prior research on PP risk in terms of stakeholders. ESRs that have received limited attention in the past are explored from an interaction perspective in the PP domain. A new two-layer FBN model considering risk causality and project dependency is proposed, which can synthesize different dependencies between projects.