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Distributed photovoltaic (DPV) projects generally have output risks, and the production effort of the supplier is often private information, so the buyer needs to design the optimal procurement contract to maximise its procurement utility.

Based on the principal-agent theory, we design optimal procurement contracts for DPV projects with fixed payments and incentive factors under three situations, i.e. symmetry information, asymmetry information without monitoring and asymmetry information with monitoring. We obtain the optimal production effort and expected utility of the supplier, the expected output and expected utility of the buyer and analyse the value of the information and monitoring.

The results show that under asymmetric information without monitoring, risk-averse suppliers need to take some risk due to output risk, which reduces the optimal production effort of the supplier and the expected output and expected utility of the buyer. Therefore, when the monitoring cost is below a certain threshold value, the buyer can introduce a procurement contract with monitoring to address the asymmetry information. In addition, under asymmetric information without monitoring, the buyer should choose a supplier with a low-risk aversion.

Considering the output risk of DPV projects, we study the optimal procurement contract design for the buyer under asymmetric information. The results provide some theoretical basis and management insights for the buyer to design optimal procurement contracts in different situations.

The primary objective of the paper is to examine the asymmetric Cointegration and asymmetric causality between financial development and poverty alleviation on annual data in Indian context over the period from 1980 to 2019.

First nonlinearity test by Brooks et al. (1999) is applied to ascertain the nonlinear behavior of the variables used. Once the nonlinear behavior of variables is confirmed, asymmetric and nonlinear unit root tests by Kapetanios and Shin (2008) are applied to check for the order of integration of selected variables. Next, nonlinear autoregressive distributed lag model (NARDL) is employed to analyze the asymmetric Cointegration. Finally, Hatemi-j- asymmetric causality tests is applied to work out the direction of asymmetric causality.

The empirical findings document the existence of asymmetries in the short-run as well as long-run between poverty and financial development. The asymmetry reveals that negative financial development shocks leave a more profound impact on poverty alleviation than their positive equivalents. The findings of Wald's test also confirm the presence of asymmetric Cointegration. The asymmetric cumulative dynamic multipliers used to examine the behavior of asymmetries and adjustments with respect to time lend credence to the results calculated using NARDL estimator. This result exhibits the robustness of the model. Furthermore, the result emanating from recently introduced asymmetric causality test reveals a unidirectional asymmetric causality between negative shocks in financial development and poverty. The findings of the present study necessitate the need for investigating asymmetric and nonlinear effects in finance–poverty nexus, which existent literature has completely neglected, in order to have relevant policy conclusions.

The study used “Per capita consumption expenditure” as a measure for poverty due to lack of continuous time series data on headcount ratio. In future, researchers can extend this study by incorporating headcount ratio as a measure of poverty in their respective works. There is further scope of research on this issue by finding out the impact of formal and informal sources of credit on poverty separately. A panel data study for developing countries over a period of time could further confirm/negate the findings of the present study.

To the best of the authors’ knowledge none of the studies in Indian context has scrutinized asymmetric and nonlinear impact of financial development on poverty. To dredge up asymmetric structures at work, the authors have used the highly celebrated NARDL estimator. To enrich the existent body of knowledge along the lines of asymmetric (nonlinear) linkages, the authors have also used recently introduced asymmetric causality test by Hatemi-j-(2012) to find out the direction asymmetric causality.

Purpose: This chapter examines the effect of COVID-19 on the stock market volatility (SMV) in the Colombo Stock Exchange (CSE), Sri Lanka.

Need for the Study: The study is necessary to understand investor behaviour, market efficiency, and risk management strategies during a global crisis.

Methodology: Utilising daily All Share Price Index (ASPI) data from 2 January 2018 to 31 August 2021, the data are divided into subsamples corresponding to the pre-pandemic period, the pandemic period, and distinct waves of the pandemic. The impact of the pandemic is investigated using the Mann–Whitney U test, the Kruskal–Wallis test, and the Exponential Generalised Autoregressive Conditional Heteroscedasticity (EGARCH) model.

Findings: The pandemic considerably affected CSE – the Mann–Whitney U test produced different market returns during the pre-COVID and COVID eras. The Kruskal–Wallis test improved performance during COVID-19 but did not continue to do so across COVID-19 waves. The EGARCH model detected increased volatility and risk during the first wave, but the second and third waves outperformed the first. COVID-19 had a minimal overall effect on CSE market results. GARCH and Autoregressive Conditional Heteroskedasticity (ARCH) models identified long-term variance memory and volatility clustering. The News Impact Curve (NIC) showed that negative news had a more significant impact on market return volatility than positive news, even if the asymmetric term was not statistically significant.

Practical Implications: This study offers significant insight into how Sri Lanka’s SMV is affected by COVID-19. The findings help create efficient mitigation strategies to mitigate the negative consequences of future events.

This study aims to evaluate the structural oil shocks effect on stock returns of Indian renewable energy companies across market conditions.

This study applies the structural vector autoregression model to estimate sources of oil shocks such as oil supply shock, aggregate demand shock and oil price-specific demand shock. In the next step, the panel quantile regression model estimates the effect of these oil shocks on stock return across market conditions. Monthly data are collected from January 2009 to December 2019. All renewable energy companies listed on the National Stock Exchange of India are considered for the analysis.

In the whole sample analysis, this study finds that oil shocks negatively affect stock returns in most of the market conditions except oil price-specific demand shock. In sub-groups, oil shocks driven by supply and aggregate demand also negatively affect stock return in most market conditions. This study finds the positive interaction of oil price-specific demand shock. A majority of these positive interactions happen in bearish market conditions. In the whole sample, the asymmetric effects of shocks driven from oil supply and oil price-specific demand are seen in most quantiles or market conditions. At the same time, aggregate demand shock does not affect asymmetrically. In the sub-group analysis, standalone renewable energy companies stock returns are least asymmetrically affected by these oil shocks. The asymmetries of oil supply-driven shock on stock returns of the renewable energy sub-group companies are found in most quantiles.

First, this is a company-level study of the stock returns response to the structural oil shocks in the renewable energy sector. Second, to the best of the authors’ knowledge, this type of study is the first in the Indian context. Third using panel quantile regression model along with capital asset pricing model framework, the authors investigate these effects across market conditions.

This study investigates augmented reality (AR) retailing and attempts to develop a profound understanding of consumer decision-making processes in AR-enabled e-retailing.

The study is grounded in rich informational cues and information processing mechanisms by incorporating the elaboration likelihood model (ELM) and trust transfer theory. This study employs a mixed analytic method that incorporates structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to provide a complete picture of individual information process mechanisms in AR retailing under the tenet of ELM.

The SEM analysis results confirm the relationships between the central and peripheral route factors, information processing outcomes and eventual behavioral intentions. Moreover, all configurations revealed by the fsQCA include both central and peripheral factors. Hence, the dual routes proposed in the ELM are verified by using two distinct analytical approaches.

This study is pioneering in validating and contextualizing ELM theory in AR retailing. In addition, this study offers a methodological paradigm by demonstrating the application of multi-analysis in exploring consumers’ information process mechanisms in AR retailing, which offers a holistic and comprehensive view to understand consumers’ decision-making mechanisms.

The paper covers the topic of power strategies between actors and the interplay between the service ecosystem and the actor(s), and vice versa. The paper addresses the lack of conceptual development concerning power considerations beyond dyadic, rigid and role-based models found in general marketing literature. Further, the paper opens the area of power relationships, using the service ecosystem as conceptual framework.

The paper has a systemic and sociological view on service-ecosystems using mainly Giddens' structuration theory. Service-dominant logic literature from 2004 to 2021 is systematically reviewed for power issues and qualitatively analyzed. Mayring's step model of, firstly, inductive and, secondly, deductive category development is applied. Subcategories were identified, subsumed and finally grouped into five categories to increase the level of abstraction.

The article investigates power considerations and enables marketers to create power through (1) imbalance, to find strategies and counterstrategies for (2) actor's behavior, to understand the (3) actor's embeddedness within a service ecosystem and its dynamic nature, to learn about (4) institutions and actor's institutional work. A set of seven propositions is presented for the conceptualization of power strategies in a service ecosystem.

The consideration of power on different levels supports both the zooming-in and zooming-out to observe and understand the power phenomena in a service ecosystem. Seven propositions about episodic as well as systemic power relations are presented. Power is conceptualized in service ecosystem as transformative capability of an actor to intervene on institutions and in some way alter them, recognizing that power relations are co-created, dynamic and context-dependent.

The article recognizes different levels (micro-meso-macro) of power considerations and helps practitioners and marketers to create power through (1) imbalance, find strategies and counterstrategies for (2) actor's behavior, understand the (3) actor's embeddedness within a service ecosystem and its dynamic nature, learn about (4) institutions and actor's institutional work. This enables managers to find an appropriate choice of action in their specific context to transform the service ecosystem(s) they are embedded in.

As all social systems are power systems, a service ecosystem can only be fully understood by integrating the elementary concept of power. As such, power considerations within actor strategies and the service ecosystem are relevant to improve the understanding of transformation of the service ecosystem. Power, in the sense of the transformative capability of actors, changes the social and material world.

Power issues are important to understand the “hows” of resource integration in service ecosystems and its transformation or stability.

This study aims to provide an excellent overview of current research trends in the construction sector in digital advancements. It provides a roadmap to policymakers for the effective utilisation of emergent digital technologies and a need for a managerial shift for its smooth adoption.

A total of 3,046 peer-reviewed journal review articles covering Internet of Things (IoT), blockchain, building information modelling (BIM) and digital technologies within the construction sector were reviewed using scientometric mapping and weighted mind-map analysis techniques.

Prominent research clusters identified were: practice-factor-strategy, system, sustainability, BIM and construction worker safety. Leading countries, authors, institutions and their collaborative networks were identified with the UK, the USA, China and Australia leading this field of research. A conceptual framework for an IoT-based concrete lifecycle quality control system is provided.

The study traces the origins of the initial application of Industry 4.0 concepts in the construction field and reviews available literature from 1983 to 2021. It raises awareness of the latest developments and potential landscape realignment of the construction industry through digital technologies conceptual framework for an IoT-based concrete lifecycle quality control system is provided.

This chapter focuses to study the aspect of dynamic profitability of the Indian computer industry in the post tariff rationalization period, i.e., complete elimination of tariff on imported computers parts and component after implementation of Information Technology Agreement (ITA) in 2004. If trade liberalization affects profitability, then it also interrupts the firm's financial structure because a firm reduces its short-run debts when it generates huge profit. On the contrary, higher marginal return or profitability of asset encourages the debtor to invest more. In fact, trade liberalization may affect investment through marginal profitability of asset by varying projected sales and costs of imported inputs, i.e., by altering the imported input price. This study examines the viable relationship between dynamic profitability and directives of the ITA. The sample selected from 51 Indian computer firms (14 hardware firms and 37 software firms) level data ranging from 2000–2001 to 2018–2019 and by application of dynamic panel data, the results are analyzed in this research work. This chapter observes that return on asset is negatively significant with the ratio between short-term liability and total liability for both the software and hardware sector of Indian computer industry in post-ITA policy timeline.

This research delves into a comprehensive examination of Amazon’s Vendor Flex (VF) model, seeking to illuminate the intricacies of supply chain innovation through alliances between Amazon and its suppliers. Employing a multiple case study methodology, the study investigates the reduction of transaction costs, the establishment of strategic alliances for supply chain innovation and governance issues within these alliances.

A multiple case study methodology, incorporating personal interviews and triangulation with primary sources, was employed to unravel the dynamics of the VF model.

Results indicate that the VF model aligns with the reduction of transaction costs by leveraging Amazon’s specialized knowledge, although not necessarily through direct knowledge sharing. Amazon suppliers highlight competitive advantages gained through VF, showcasing efficient navigation of peak seasons and a focus on core activities with online retailing integration. The VF alliance represents a collaborative model where Amazon’s technological prowess enables a streamlined and innovative supply chain for online retailing, which resembles a vertical integration process.

This research underscores the potential of strategic alliances to drive innovation by incorporating industry-leading practices. The governance issues within the VF alliance reveal power imbalances, emphasizing the need for managers to govern dynamics, disclose information and build trust in large-scale alliances.

This study aims to explore whether and how the two potential antecedents (i.e. relationship quality at the dyadic level and network density at the network level) affect firms’ internet-interactive capability (FIIC), referring to the capability of a specific firm to communicate and interact with the relevant partner firms on the basis of internet-interactive technologies in the internet environment and, at the same time, the following influence of FIIC on collaborative activities (i.e. joint planning and joint problem-solving).

This study designed a questionnaire and collected data on-site from 400 manufacturers. SmartPLS is used to validate the research model.

The results suggest that the dyadic relationship quality and network density of the partner group are both positively connected with a firm’s FIIC. Besides, FIIC is positively related to collaborative activities with its partners.

Given the nature of our data (i.e. cross-sectional), the authors can collect longitudinal or experimental data to retest the hypotheses.

This study gives certain guidance for firms to be aware of the factors that motivate FIIC and use their FIIC to influence their employees’ collaborative activities in their relationships with partners, thereby promoting cooperation performance.

This study attempts to extend the resource-based theory based on the logic of motivation-capability by exploring the potential antecedents of FIIC and makes contributions to the current studies on the antecedents of FIIC, which provides actionable insights for firms to play the role of FIIC in interfirm interactions.