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Higher education has seen an unprecedented amount of change in recent decades, with technological advancements impacting on the very essence of teaching and learning. As there are an abundance of digital tools available to educators, it can be a challenge to select the most appropriate online platforms to incorporate into the classroom. This chapter discusses the topic of digital storyboarding by providing a case study of how the author adopted the online platform Storyboard That to enhance student engagement and co-creativity within a UK higher education institution. The chapter debates the benefits and challenges of technology-enhanced learning as part of a blended approach, and concludes with advice for educators wishing to adopt digital storyboarding within their own educational context.

This chapter reviews graphical modeling techniques for estimating large covariance matrices and their inverse. The chapter provides a selective survey of different models and estimators proposed by the graphical modeling literature and offers some practical examples where these methods could be applied in the area of health economics.

Introduction: The current study examines the relationship of reciprocity and the knowledge sharing behavior (KSB) with the mediating role of organizational commitment.

Aim: The purpose of this chapter is to examine linkages between reciprocity and KSB in Pakistani Pharmaceutical industry basing on social exchange theory (SET) (Blau, 1964). Employees’ affective and normative organizational commitments were proposed as mediator to explain these relationships.

Method: Data were collected using Survey Questionnaires from a sample of 287 managers and staff of sales department of different pharmaceutical firms in Rawalpindi and Islamabad, Pakistan. This is an explanatory study with a quantitative approach. KSB model was developed and tested using a two-stage analysis. Initially, path analysis using AMOS was carried out followed by mediation through process analysis.

Findings: Affective and normative commitment was found to be mediating between reciprocity and KSB using SET.

Originality of the Study: Few empirical studies have analyzed the effects of reciprocity on KSB, especially in context of pharmaceutical industry. Mediation of employee’s commitment could provide new insights to management practitioners in fostering KSB.

Implications: The finding will allow organizations in general and pharmaceutical firms in particular, to focus more on commitment toward their employee as a reciprocal benefit for improving knowledge sharing culture in their organizations.

Research on international experience notes its positive influence on subsequent international expansion by firms. We test this relationship in the context of the Indian software industry whose offerings, unlike many other services, are storable implying that delivery can be separated from production.

We analyzed the domestic expansion of a sample of publicly listed Indian software firms over the period 2000–2009 with help of Poisson regression.

We find that even internationally experienced Indian software firms might prefer to expand domestically because of limited financial and managerial resources and concerns about diluting their cost advantage. The storable and separable nature of software services will support this strategy of serving clients remotely. The domestic expansion of assets will, however, be slower for firms with the highest level of industry accreditation. It will also be slower if there are institutional pressures in the form of rivals locating development centers near clients in developed countries.

Our results demonstrate that international experience alone is not sufficient for firms to expand overseas.

Peer-to-Peer (P2P) lending, which makes borrowers and investors meet directly through online platforms bypassing traditional financial institutions, is an emerging financing market after the traditional financial institutions crushed during the global financial crisis from 2007 to 2009. P2P lending platforms meet the credit demand more efficiently and play a vital role for the credit market and economic activity. This study sheds light on whether the credit spread of P2P lending is well predictive of economic activity compared to the bond credit spread which has been fully investigated in prior studies. Our findings show that the P2P credit spread performs similarly in predicting the economic activity as bond credit spread only during the financial crisis. However, the predictive power of P2P credit spread becomes inverse during the noncrisis periods since P2P lending platforms provide an alternative and easier financing channel to individuals who hardly borrow money for refinancing from traditional financial institutions. This study highlights the alternative role of P2P lending platform in financing and provides the evidence of different predictive powers of P2P credit spread on economic activity in different time periods.

This study traces the boundaries of online-based social networks and its possible extensions and intersections with offline social networks. It focuses on the massive multiplayer online (MMO) gaming community. Most online gaming research has only addressed one side of the equation, that is, the online aspect of social interaction, omitting the offline context. The primary objective is to look at both offline and online social contexts of gamers. The data analyzed here are part of a bigger research project. Using a sample of 242 respondents and a total of 1,452 social ties (three online and three offline) this work addresses the differences and similarities between online gamer’s offline and online networks. Around 72% of the participants were between the ages of 18 and 37. This group provides insight into the management of social interactions and ties in the digital age among millennials and the coming-of-age of Generation Z. The analysis suggests that overall offline ties are slightly more important than online. Still, this does not imply that online ties are not meaningful at all. The length of their online relationships plays a significant role in how participants qualify their ties. Most participants that had not met face-to-face were willing to meet their online ties. They also reported sharing personal and everyday life matters with their online social network at a lower rate of their offline network. Time spent with online relationships stemming from online gaming and a cooperative environment is more likely to be considered higher quality time. This suggests that in MMOs the gap between online and offline relationships is becoming narrower.

One aspect of the opportunities and challenges for cryptoassets concerns decentralized finance (DeFi). DeFi is a growing area of cryptoassets that couples blockchain technology, digital assets, and financial services. DeFi is a publicly available system on a decentralized blockchain network, offering financial products and applications. This chapter provides an overview of the DeFi universe that has enormous potential in various industries in the global market. It also discusses the implications of DeFi’s new wave and its applications involving initial coin offerings and stablecoins and specific challenges like the scalability trilemma in DeFi and financial markets.

This paper addresses the issue of improving the forecasting performance of vector autoregressions (VARs) when the set of available predictors is inconveniently large to handle with methods and diagnostics used in traditional small-scale models. First, available information from a large dataset is summarized into a considerably smaller set of variables through factors estimated using standard principal components. However, even in the case of reducing the dimension of the data the true number of factors may still be large. For that reason I introduce in my analysis simple and efficient Bayesian model selection methods. Model estimation and selection of predictors is carried out automatically through a stochastic search variable selection (SSVS) algorithm which requires minimal input by the user. I apply these methods to forecast 8 main U.S. macroeconomic variables using 124 potential predictors. I find improved out-of-sample fit in high-dimensional specifications that would otherwise suffer from the proliferation of parameters.

This research constructs the critical predictors of visitation that shall allow the practitioners to foresee the visitation in the years to come through secondary data. For this study, tourist arrival data associated with the most popular forest park (i.e., Xiton Forest Park) in Taiwan along with relevant socio-economic data are utilized. This research adopts a group of analytical procedures involving correlation analysis, regression, and curve estimation analyses. The results show that the number of holiday per month and the average monthly rainfall have positive and negative correlations, respectively, with the visitation. Meanwhile, average monthly temperature and monthly gross domestic product per capita show a positive correlation in all three analytical methods and therefore are regarded as the primary predictors of tourist arrival. Consequently, this study provides managerial implications to increase the tourist arrivals to the forest park.