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This chapter examines the introduction of Electronic Voting Systems (EVS) at a UK university with the aim of promoting and supporting the student learning experience and moving from an ‘ad hoc’ and individual basis for the use of EVS at the local school level to offering support for using and developing their use on a wider institutional basis. Following discussion of the research into EVS adoption and use, the authors propose a framework to be used by those academics and managers in higher education institutions (HEI) who are interested in introducing specific technologies to support learning, such as the EVS. The framework incorporates a three-way focus on the development of a robust technology infrastructure, the provision of support and training for those using new technologies, placed within the context of sound change management principles and thus supported by the research into these areas. Previous studies in Europe, the United States and Canada into the use of EVS as, for example, in the REAP (Re-Engineering Assessment Practices) project (Nicol & Draper, 2009) have indicated that students are enthusiastic about their use in the lecture hall and seminar room and that the creative use of EVS by academics enhances their use to stimulate and support a number of classroom interactions. To date, however, there has been a lack of research studies on institutional deployment of EVS. This work is intended to outline the salient issues and start that conversation.

The case would be relevant to undergraduate level or an introductory master's level course in operations management (OM), supply chain management and production.

The case can be used as part of a core OM course in the MBA curriculum or any OM or supply chain elective.

As a highly diversified manufacturing services company, Jabil's S&OP solution supports customers across many industries such as automotive, cloud computing, consumer packaging, healthcare, mobile, retail and telecommunications. Jabil's customers expect a rapid and accurate response to their demand within hours. Previously, Jabil used a series of legacy disconnected planning tools, unsynchronized data required time-consuming manipulation with Excel. Processes were conducted in siloes leading to a “load and chase” approach, which resulted in excess inventory, component shortages and inadequate capacity. The case focuses on one of the Jabil executives, Lizet Tymon (she). Struggling with the issues caused by the disconnected planning tools, Lizet champions implementing a fully integrated suite of services (built on top of the Kinaxis' RapidResponse software platform). The technology solution proposed by Lizet was ultimately implemented across the company, and the project received high marks, and it opened up career opportunities for her. However, it was not a smooth ride at the very beginning. The case focuses on the issues experienced by Lizet, as she is introducing a new technological solution approach and trying to earn support from her team, her peers, her immediate supervisor, her customers and her higher-level executives.

The teaching objectives include: understanding and appreciating the supply chain complexities experienced by a global contract manufacturer; helping students think critically regarding the issues around the sales and ops planning; identifying the data needs for the operation and management of a worldwide, connected supply chain; investigating agile solution approaches for information sharing, decision-making and decision-sharing; and exposing the challenges associated with a large-scale technology adaptation.

This case study describes the supply chain challenges experienced by a global manufacturing solutions provider and illustrates the technology adaptation led by a female executive.

Teaching Notes are available for educators only.

CSS 9: Operations and Logistics

The purpose of this paper is to understand the nature of the feedback effects of economic growth on innovation. The question is whether the economies with higher levels of endowments have a declining feedback effect of income on innovation and contribute to the development of effective innovation policies are raised.

This study hypothesizes that innovation input’s response to economic growth in terms of income is an inverted “U” shaped path, whereas the innovation output’s response to income is positive and asymptotic. This paper uses the global innovation index data of 154 countries over the period 2013–2017 on innovation and gross domestic product for the analysis using the fixed-effect regression models.

The results confirmed the inverted U shaped relationship in the line of Kuznets’s curve for innovation input and that of negative slope and asymptotic behaviour for innovation output.

In this study, the analysis performed using the global innovation index 2013–2017 data. This study can be extended at each factor level to understand this phenomenon in depth with more data and to help in improving the innovation policies for the betterment of the economic growth.

This study suggests that developed countries need to guard against complacency in their innovation efforts because of the asymptotic nature exhibited through the effective development of innovation policies. The developing economies can look forward to establishing themselves in the domains of innovation input through imitation of technologies.

This paper extends the study of feedback effects of economic growth on innovation. This study brings out the nature of feedback effects of economic growth on input innovation and output innovation activities. The results show a declining feedback effect of income on innovation in economies with a higher level of endowments and highlight the inclusion of feedback effects of economic activities on the innovation while designing the innovation and economic policies of a country.

This study aims to examine the psychometric properties of the Cyberbullying Attitude Scale (CBAS) in Indian college students with the help of two independent studies.

The first study investigated the factorial validity of the scale using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), resulting in a seven-item, two-component model of CBAS. Two statements were excluded owing to inadequate factor loading. The second study evaluated the reliability and criterion validity of the model extracted after CFA using the Weight-Based Teasing Scale (WBTS), PhQ9 as convergent indices and Gratitude Questionnaire 6 (GQ6) as divergent indices.

It was observed that the Indian version of the scale differs from the original version in two ways. First, the Indian CBAS comprised seven items, while the original CBAS consisted of nine items. Second, in the original CBAS, two factors of cyberbullying, i.e. hostile cyberbullying attitudes (HCA) and general cyberbullying characteristics (GCC), contained five and four statements, respectively. However, the Indian CBAS comprised five and two statements, respectively. Further, the Indian CBAS showed convergence with WBTS and PhQ9 and divergence with GQ6.

This study is one of the first to explore the psychometric properties of Indian CBAS and its relations with teasing and gratitude.

While the peer effects of technology adoption are well established, few studies have considered the variation in peer effects resulting from the mutual proximity between leaders and followers and the heterogeneity of farmers' learning technology. This study addresses the gap in the literature by analyzing the peer effects of technology adoption among Chinese farmers.

Drawing on a government-led soil testing and formulated fertilization program, this study uses survey data of farmers from three Chinese provinces to examine the peer effects of technology adoption. This study uses a probit model to examine how mutual proximity influences peer effects and their heterogeneity. Accordingly, farmers were divided into two groups, namely small- and large-scale farmers, and then into leaders or followers depending on whether they were selected by the government as model farmers.

Both small- and large-scale farmers are more likely to use formula fertilizer if their peers do so. However, a large-scale farmer is more likely to adopt formula fertilizer if the average adoption behavior of other large-scale model (leader) farmers is higher, while a small-scale farmer is more likely to adopt formula fertilizer if other small-scale non-model (follower) farmers have higher average adoption behavior. Moreover, the peer effect was weakened by geographic distance among small-scale farmers and by economic distance among large-scale farmers.

This study elucidates the means of optimizing social learning and technology adoption among farmers.

This paper aims to study low adoption of modern technology for pearl millet in Rajasthan, India, from the perspective of social networks. The state has the lowest adoption of modern pearl millet seeds among Indian states. . In particular, this paper tries to identify the limitations of channels with endogenous effects, thereby limiting large-scale adoption of modern varieties that would require social multipliers.

Defining the network/reference groups in terms of social identity and geographical proximity, this paper utilizes the intensity of interaction with different network nodes to identify the presence of endogenous effects. In particular, this paper uses the interaction of intensity of social exchange with the group level adoptions to establish the presence of endogenous effects. With adequate controls, greater intensity of interaction having a bearing on technology choice can only happen when there exists social learning (endogenous effect) and cannot be associated with other forms of social effects (namely, exogenous and correlated effects).

This paper finds evidence for the existence of endogenous social effects in adoption but largely from exclusionary channels. A comprehensively mapped network is used with its intensity to explain the extremely low rate of adoption. Only close-knit networks that, with social fragmentation, limit benefits to few, affect adoption significantly. The non-functionality of less exclusionary information sources and services can be a factor underlying low adoption.

The main limitation of the study is inability to control for unobserved individual heterogeneity because of the cross-sectional nature of data. Further, although an extensive mapping of individual networks has been done, it still cannot be guaranteed to be exhaustive.

With fragmentation, large-scale adoption programs would require networks, sources of information and services that are less exclusionary. Based on the survey data, media and non-religious organizations play a focal role here in the adoption of modern technology. This finding is extremely crucial for policy, as these channels comprise direct policy levers in a fragmented society like India. Indeed, several government programs in India have relied on these channels to run large-scale adoption programs. Their ineffectiveness could be a prime factor for such limited dissemination of technology in Rajasthan.

In different settings, social fragmentation could be an important factor determining technology adoption outcomes. The evolving consensus in the literature based on several studies is that ethnic fragmentation has potentially negative consequences on macro-economic performance (Alesina and Tabellini, 1989 and Collier, 2000). In the literature on technology adoption, the role of fractionalization is somewhat under-studied. With fragmentation, there can be significant micro-level impacts (for instance, low technology adoption of a crop) if channels that are inclusive are not well developed. The finding that channels like extension services, media or organizations are not effective in determining choice of technology does not mean that they should not be tapped. The empirical findings suggest that, in their current form in the state of Rajasthan, the roles played by these are limited. The policy implications would be to develop these systems in a way that there is a greater uptake. Recall that less than 4 per cent of the respondents got information on seeds from media sources, an extremely low number. There is certainly scope for increasing the outreach of these channels that are much more important for spread of agricultural technology in a fragmented society.

This paper is an attempt to come up with an empirical strategy to mitigate the issues related to reflection problem. In the cross-sectional data itself, we use the interaction of group choices with intensity of interaction within the group to introduce a non-linearity that tries to bypass the identification issues as in reflection problem. This method of introducing non-linearity in cross-sectional data is a novel attempt to achieve identification of endogenous effects.

This paper aims at identifying the key factors influencing the adoption intention of data analytics for predictive maintenance (PdM) from the lens of the Technology–Organization–Environment (TOE) framework in the Singapore Process Industries context. The research model aids practitioners and researchers in developing a holistic maintenance strategy for large-scale asset-heavy process industries.

The TOE framework has been used in this study to consider a wide set of TOE factors and develop a research model with the support of literature. A survey is undertaken and the structural equation modelling (SEM) technique is adopted to test the hypotheses of the proposed model.

This research highlights the significant roles of digital infrastructure readiness, security and privacy, top management support, organizational competence, partnership with external consultants and government support in influencing adoption intention of data analytics for PdM. Perceived challenges related to organizational restructuring and process automation are not found significant in influencing the adoption intention.

This paper reports valuable insights on adoption intention of data analytics for PdM with relevant implications for the various stakeholders such as the leaders and senior managers of process manufacturing industry companies, government agencies, technology consultants and service providers.

This research uniquely validates the model for the adoption of data analytics for PdM in the process industries using the TOE framework. It reveals the significant technology, organizational and environmental factors influencing the adoption intention and highlights the relevant insights and implications for stakeholders.

This paper aims at understanding the causes of low adoption of hybrid rice technology. The paper also assesses the impact of adoption of hybrids and modern varieties on crop yield, vis-à-vis the old or traditional varieties.

Using unit-level data from a large-scale survey of farm households (19,877 paddy cultivators), the authors applied multi-nomial regression method to understand the factors for adoption of hybrid rice and instrumental variable method of regression to estimate its impact.

The findings demonstrate that in India, hybrid rice is often grown on relatively poor soils, resulting in greater irrigation costs and for other inputs, such as fertilizers. Further, farmers' poor access to information on the traits of hybrid rice and the associated agronomic practices, as well as poor access to financial resources, hampers efforts to scale up its adoption. More importantly, the findings reveal that the relative yield advantage of hybrids over open-pollinated modern varieties is not large enough to incentivize the rapid adoption of hybrid rice technology.

Given the higher cost of hybrids than the inbred varieties, enhancing paddy cultivators' access to financial resources can accelerate the adoption of hybrid rice in India.

The study is based on unit level data from a large-scale, nationally representative survey of farm households, comprising a sample of 19,877 paddy cultivators, spread across states in India.

Smart card-based E-payment systems are receiving increasing attention as the number of implementations is witnessed on the rise globally. Understanding of user adoption behavior of E-payment systems that employ smart card technology becomes a research area that is of particular value and interest to both IS researchers and professionals. However, research interest focuses mostly on why a smart card-based E-payment system results in a failure or how the system could have grown into a success. This signals the fact that researchers have not had much opportunity to critically review a smart card-based E-payment system that has gained wide support and overcome the hurdle of critical mass adoption. The Octopus in Hong Kong has provided a rare opportunity for investigating smart card-based E-payment system because of its unprecedented success. This research seeks to thoroughly analyze the Octopus from technology adoption behavior perspectives.

Cultural impacts on adoption behavior are one of the key areas that this research posits to investigate. Since the present research is conducted in Hong Kong where a majority of population is Chinese ethnicity and yet is westernized in a number of aspects, assuming that users in Hong Kong are characterized by eastern or western culture is less useful. Explicit cultural characteristics at individual level are tapped into here instead of applying generalization of cultural beliefs to users to more accurately reflect cultural bias. In this vein, the technology acceptance model (TAM) is adapted, extended, and tested for its applicability cross-culturally in Hong Kong on the Octopus. Four cultural dimensions developed by Hofstede are included in this study, namely uncertainty avoidance, masculinity, individualism, and Confucian Dynamism (long-term orientation), to explore their influence on usage behavior through the mediation of perceived usefulness.

TAM is also integrated with the innovation diffusion theory (IDT) to borrow two constructs in relation to innovative characteristics, namely relative advantage and compatibility, in order to enhance the explanatory power of the proposed research model. Besides, the normative accountability of the research model is strengthened by embracing two social influences, namely subjective norm and image. As the last antecedent to perceived usefulness, prior experience serves to bring in the time variation factor to allow level of prior experience to exert both direct and moderating effects on perceived usefulness.

The resulting research model is analyzed by partial least squares (PLS)-based Structural Equation Modeling (SEM) approach. The research findings reveal that all cultural dimensions demonstrate direct effect on perceived usefulness though the influence of uncertainty avoidance is found marginally significant. Other constructs on innovative characteristics and social influences are validated to be significant as hypothesized. Prior experience does indeed significantly moderate the two influences that perceived usefulness receives from relative advantage and compatibility, respectively. The research model has demonstrated convincing explanatory power and so may be employed for further studies in other contexts. In particular, cultural effects play a key role in contributing to the uniqueness of the model, enabling it to be an effective tool to help critically understand increasingly internationalized IS system development and implementation efforts. This research also suggests several practical implications in view of the findings that could better inform managerial decisions for designing, implementing, or promoting smart card-based E-payment system.

Adopting additive manufacturing (AM) can be challenging, especially in small- and medium-sized enterprises (SMEs) and as part of the supply chains of larger firms. The purpose of this paper is to explore SMEs’ perspectives on the adoption of AM in their specific supply chain positions. The paper develops new knowledge on the challenges SMEs face across the supply chain and the actions they need to promote the adoption of AM.

An exploratory interview-based research design is used. In total, 17 interviews were conducted and analyzed in four types of SMEs in their specific positions in AM supply chains. The challenges of adopting AM were mapped, and actions to promote AM adoption were identified.

SMEs in different supply chain positions experience different challenges when adopting AM. Strategic and operative actions are suggested as key solutions to overcome the challenges. The benefits of AM on a large scale will be achieved only if the broader supply chain adopts AM technology and experiences its benefits.

The research is limited by its single-country context, its focus on SMEs, and the selection of early-phase AM-adopter firms. The findings imply a need to understand AM adoption as a shared concern and systemic innovation in the supply chain, instead of just a firm-specific implementation task.

The findings offer a framework for categorizing AM adoption challenges and propose ways to overcome the challenges of adoption.

The study reveals that AM adoption is not only a technology issue, but also an issue of strategic, organizational and operational challenges across the supply chain. It shows that when adopting AM, SMEs face particular challenges and require specific solutions according to their supply chain position.