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Informed traders may prefer the options market to the stock market for reasons including the leverage effect, transaction costs, restrictions on short sale. Many studies try to predict future returns of stocks using informed traders' behavior in the options market. In this study, we examine whether the trading volume ratios of single stock options have the predictive power for future returns of the underlying stock. By analyzing the stock price responses to the “preliminary announcement of performance” of 36 underlying stocks on the Korea Exchange from November 2014 to March 2021 and the trading volume of options written on those stocks, we investigate the relation between the option ratios, which are the call option volume to put option volume ratio (C/P ratio) and the option volume to stock volume ratio (O/S ratio), and the future returns of the underlying stock. We also examine which ratio is better in predicting the future returns. The authors found that both option ratios showed the statistically significant predictability about future returns of the underlying stock and that the return predictability of the O/S ratio is more robust than that of the C/P ratio. This study shows that indicators generated in the options market can be used to predict future underlying stock returns. Further, the findings of this study contributed to a dearth of literature pertaining to single stock options. The results suggest that the single stock options market is efficient and influences the price discovery in the stock market.

Within digital innovation, there are two significant consequences of the pervasiveness of digital technology: (1) the increasing connectivity is enabling a wider reach and scope of innovation structures, such as innovation networks and (2) the unprecedented availability of digital data is creating new opportunities for innovation. Accordingly, there is a growing domain for studying data-driven innovation (DDI), especially in contemporary contexts of innovation networks. The purpose of this study is to explore how DDI processes take form in a specific type of innovation networks, namely federated networks.

A multiple case study design is applied in this paper. We draw our analysis from data collected over six months from four cases of DDI. The within-analysis is aimed at constructing the DDI process instance in each case, while the crosscase analysis focuses on pattern matching and cross-case synthesis of common and unique characteristics in the constructed processes.

Evidence from the crosscase analysis suggests that the widely accepted four-phase digital innovation process (including discovery, development, diffusion and post-diffusion) does not account for the explorative nature of data analytics and DDI. We propose an extended process comprising an explicit exploration phase before development, where refinement of the innovation concept and exploring social relationships are essential. Our analysis also suggests two modes of DDI: (1) asynchronous, i.e. data acquired before development and (2) synchronous, i.e. data acquired after (or during) development. We discuss the implications of these modes on the DDI process and the participants in the innovation network.

The paper proposes an extended version of the digital innovation process that is more specifically suited for DDI. We also provide an early explanation to the variation in DDI process complexities by highlighting the different modes of DDI processes. To the best of our knowledge, this is the first empirical investigation of DDI following the process from early stages of discovery till postdiffusion.

Over the past few decades, university reforms in line with management and enterprise ideals have been well documented. Changes in the ideals underlying the missions of universities have led to changes in their modes of governing and organizing, which in turn drive further transformation of their missions. One set of reforms in Swedish higher education has been the dissolution of collegial bodies and procedures. At the same time, in recent years, we have witnessed an increased interest in collegiality and a reintroduction of collegial bodies and procedures. New translations of collegiality appear not only in how universities are organized, but also in other core aspects of research and higher education. We review examples of peer reviewing, research assessment, and direct recruitment of professors and ask: Can these new translations of collegiality be understood as a revitalization of collegiality, or is it – to draw a parallel with greenwashing – rather a matter of collegiality-washing?

This paper is a corpus-driven study of written electronic texts, particularly the “About Us” sections in the university websites of 41 members of the Asian Association of Open Universities (AAOU). This inquiry is important because it will provide an insight as to how AAOU members describe and portray themselves in the World Wide Web, a platform which is highly utilized in the field of distance education. This will also lead to the understanding of conventional knowledge among AAOU members during the period of study. The paper aims to discuss these issues.

Guided by Swales’ (1990) seminal work on genre analysis, the researchers conducted a three-part genre analysis which involved identification and analysis of moves, keywords, and concordance lines.

Results of the keyword analysis were conducted using the AntConc application. Anthony (2017) found that the top 100 keywords with positive keyness exemplified inherent characteristics of open and distance learning institutions as well as characteristics common to higher education institutions and their thrusts. The analysis also found that the use of adjectives and verbs with positive denotations is common in the “About Us” sections. Concordance for several keywords related to the overarching theme of the AAOU 2017 Conference then revealed that the AAOU members are active in the discourse about accessibility, assessment, and quality, while there is not much discourse on openness, inclusivity, and justice. Meanwhile, subscribing to equality and equity could still be a point of discussion among the AAOU members as the concordance analysis revealed more discourse on equality than equity as a goal and principle. Overall, results of the genre analysis resonated with previous studies of the academic genre as the “About Us” sections are promotional in both authoritarian and inclusive ways.

The inquiry will provide the members of the AAOU with an overview of their common communicative purposes, overused or underused keywords, and their usage of these words which they may opt to work on in the future.

This study aimed at analyzing the factors that induce the intention of contribution by participants in crowdsourcing initiatives.

This study is an explanatory investigation using a quantitative approach. In the second stage, an exploratory study was carried out. Data were obtained through online questionnaires available to the contributors of two platforms, and results were obtained from a regression analysis.

The results revealed a greater importance given by participants to intrinsic motivational factors (learning, fun and satisfaction) compared with the extrinsic motivational factor (acknowledgment). Monetary rewards proved irrelevant in this process, whereas attitude and self-efficacy proved good predictors of the intention of contribution in crowdsourcing initiatives.

No study, as far as the authors’ knowledge extends, has been undertaken to understand what motivations are more relevant in the context of crowdsourcing platforms using multiple theories.

This study aims to document students’ supply chain solutions developed through the internship hackathon program. The study profiled innovative solutions developed by university students in Kenya to solve health supply chain logistics challenges during and beyond COVID-19. This is done by exploring students’ experience in developing sustainable logistics and supply chain management capacity-building programs in a low-middle-income country (LMIC).

This study used a qualitative approach to explore the experiences and perceptions of students and mentors who participated in a hackathon program. The study followed a cross-sectional descriptive survey design, collecting data from the participants through online questionnaires. The data were analyzed and presented using thematic analysis and narrative techniques.

Findings provide preliminary evidence for narrowing the gap between theory and practice through a hackathon internship blended with a mentorship program. Assessment of this program provides evidence for developing solutions toward ensuring the availability of essential medicine in LMICs during a pandemic such as COVID-19 by students. The profiled solutions demonstrate a broader perspective of innovative solutions of university students, mentors and potential opportunities for a triple helix approach to innovation for health supply chain system strengthening.

This original study provides evidence for advancing contribution to developing innovative solutions through partnerships between investors, universities and industry practitioners interested in mentoring students in the health-care supply chain during COVID-19 in LMICs. Specifically, contingency factors that affect the implementation of innovative programs during and beyond global pandemics such as COVID-19 by students’ innovators are identified, and implications for policy action are discussed based on the praxis of sensemaking.

This study examines a novel approach that combines internship, mentorship and hackathon projects for logistics and supply chain students in LMICs. The approach aims to bridge the gap between theory and practice and to create innovative solutions for essential medicines during and after COVID-19. The study urges more resources for supporting such programs, as they benefit both academia and industry. The study also argues that hackathon internship programs can help the logistics and supply chain industry adapt to the post-pandemic era. The study offers insights for investors, universities and practitioners in the health-care industry.

This study shows how to develop innovative solutions for the health-care supply chain during COVID-19 in an LMIC through partnerships between investors, universities and industry practitioners who mentor students. The study identifies the contingency factors that influence the success of such programs during and beyond global pandemics such as COVID-19 and discusses the policy implications based on the sensemaking praxis of the student innovators.

The study applied the Unified Theory of Technology Acceptance and Use Theory 2 (UTAUT2) to predict blended learning acceptance by students in universities in Zimbabwe. Blended learning is a heterogeneous mode of teaching and learning that combines face-to-face (F2F) and online modes. Owing to advances in technology, and recently, the advent of pandemics, such as COVID-19, the need for multimodal teaching approaches, such as blended learning, to enhance access to education in universities has become very important.

A quantitative approach that used a structured questionnaire for data collection from a sample of 432 postgraduate students was used. Data validation was done using confirmatory factor analysis (CFA). The structural equation modelling technique was used for data analysis.

Results showed that out of the seven factors of the UTAUT2, the factors such as performance expectancy, effort expectancy, social influences, facilitating conditions and hedonic motivation significantly and positively influenced the behavioural intentions of students in universities to accept blended learning. On the other hand, habit and price value did not significantly influence university students' behavioural intentions to accept the bended learning mode. It was further shown in the study that behavioural intentions significantly influenced the acceptance of blended learning by university students. In light of the above results, it was concluded that the UTAUT2 could be used to predict the acceptance of blended learning by university students.

The main study limitation was that it was only carried out at universities that had information and communication technology (ICT) infrastructure challenges owing to the fact that the economic situation in Zimbabwe is depressed. Limited ICT infrastructure in the universities might have had some impact on the nature of behavioural intentions of students to accept blended learning as a learning mode. Further research could be carried out in countries with better economies that are able to fund ICT infrastructures of their universities and to establish whether the results of the current study could either be confirmed, disconfirmed or enriched.

The paper suggests that universities need to increase investment in ICT infrastructure as well as in capacitating students with the necessary ICT skills for the effective use of institutional ICT when learning using the blended learning mode. Without adequate and appropriate ICT infrastructure as well as necessary ICT skills, students may develop low motivation levels and negative attitudes towards blended learning, which may eventually may affect their acceptance of the learning mode.

There is no known study that has been conducted using the UTAUT2 to establish antecedents of behavioural intentions of students to accept blended learning in the context of Zimbabwean universities. This study therefore opens new ground on factors influencing the acceptance of blended learning in the context of Zimbabwean universities. Also, the results showed that habit and price value do not significantly contribute to the behavioural intentions of university students to accept blended learning, which is not consistent with findings of past studies. This inconsistency opens new opportunities for further studies on the conditions under which these two factors can be used to significantly contribute to the development of behavioural intentions of students to accept blended learning.

This paper investigates the lead-lag relationship between the call-put options open interest value ratio and the KOSPI 200 Index returns. In addition, we tried to find whether the open interest value ratio has the information contents about KOSPI 200 Index return. When estimating call-put options open interest value ratio, we use Chen, Lung, and Tay (2005, 2009) models. The sample period covers from January 5, 1998 to December 28, 2006 with the closing price returns of KOSPI 200 Index and the open interest of the KOSPI 200 options. We use statistical methodology such as VAR (vector autoregressive model), Granger causality test, impulse response and variance decomposition model for the dynamic empirical tests.

Followings are the major findings and implications drawn from the empirical analysis of the Korean options market. Most previous researches claims that options open interest can provide the information contents to estimate the KOSPI 200 spot price movement. However, unlike the results of most previous researches, we found that the call-put options open interest value ratio does not have the information contents predicting the KOSPI 200 index return where as KOSPI 200 spot price leads the call-put options open interest value ratio.

The purpose of this paper is to systematically review the existing research and summarize the value co-creation mechanism between enterprises and users in crowdsource-based open innovation (COI).

Crowdsourcing is an effective means for enterprises to launch open innovation. This paper will first introduce the concepts and forms of open innovation and crowdsourcing, and then define COI.

This paper will analyze the key parties in innovative tasks, value co-creation mechanism that creates ideas, the interaction of key participants and the process of integrating internal and external resources to realize open innovation.

In the end, this paper will put forward the theoretical framework for future studies on the development of COI from the perspective of value co-creation.

This thesis will first introduce the concepts and forms of open innovation and outsourcing and then define COI. Then it will systematically review the existing research studies and summarize the value co-creation mechanism between enterprises and users under COI model by analyzing the key parties in innovative tasks, value co-creation mechanism that creates ideas, the interaction mode of key participants and the process of enterprises integrating internal and external resources to realize open innovation.