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Linkages play a strategic role in improving actor disposition and resource density in university–industry ecosystems. Due to the importance of interconnected ecosystems for the development of engaged universities, applying the service-dominant logic (SDL) perspective, the authors aim at developing theory on linkages that lead to a higher level of actor commitment and in turn result in increased actor disposition and greater resource density.

Data from semistructured interviews from four in depth case studies, known internationally as successful cases of university linkages development (Columbia Lab-to-Market Accelerator Network, Oxford University Innovation, Auckland Uniservices and the Münster Center for Interdisciplinarity), undergo qualitative analysis according to the Gioia methodology.

The results represent a contribution to the theory, as they highlight the strategic role of linkages in improving actor disposition and increasing resource density. Due to its shown importance, linkage is an element to be considered on its own in the innovation ecosystems configurations in the context of universities.

The results of the research have implications for university management, since they focus on how resources are mobilized and linked. The interactive roles of actors in ecosystems imply that the locus of value creation moves beyond the borders of the organization toward the linkages. Strategies for managing university–industry linkages (UIL) are presented.

To date there has not been sufficient theoretical or empirical contribution in the university–industry ecosystem context about the role of linkages to improve resource density through increased actor disposition.

This paper aims to investigate the innovation pathway of gerontechnological enterprises under the market-organization-technology (MOT) perspective through configuration analysis.

Based on the analytical framework of technology, organization and market, this paper conducts configuration analysis on the cases of 55 elderly-friendly enterprises in China combined with fuzzy-set qualitative comparative analysis (fsQCA).

First, this study identifies the three first-level preconditions affecting innovation performance: organization's architectural innovation, technology adapting to aging and market environment attention on the innovation pathway of gerontechnological enterprises. These three first-level conditions include six sub-conditions. Second, this study investigates three innovation pathways by analyzing the configuration effects of preconditions: Configuration 1, technology-balanced type; Configuration 2, organization-market linkage type and Configuration, 3 balanced type. Third, there are differences in the distribution of different configuration types in subdivided industries. The technology-balanced configuration is mainly concentrated in design-driven innovative enterprises, the organization-market linkage configuration is mainly concentrated in medical auxiliary equipment enterprises and the balanced configuration is mainly concentrated in smart elderly care service platform enterprises empowered by digital technology. Fourth, there are differences in the innovation impact paths of the same configuration type. However, the essence lies in the high-level innovation performance formed by the coordinated evolution of technology, organization and market factors, reflecting the characteristics of the same goal through different routes.

The authors' study generates new insights for innovation managers of gerontechnological enterprises about the innovation pathway.

This research enriches innovation management by integrating the linkage adaptation relationship among market, organization and technology factors; further research studies on the different configuration types suitable for different types of enterprises, as well as differentiated innovation pathways under the same configuration type, could contribute to the study on the innovation pathway under a premise of MOT.

Parallelogram linkages are used to increase the stiffness of manipulators and allow precise control of end-effectors. They help maintain the orientation of connected links when the manipulator changes its position. They are implemented in many palletizing robots connected with binary, ternary and quaternary links through both active and passive joints. This limits the motion of some joints and hence results in relative and negative joint angles when assigning coordinate axes. This study aims to provide a simplified accurate model for manipulators built with parllelogram linkages to ease the kinematics calculations.

This study introduces a simplified model, replacing each parallelogram linkage with a single (binary) link with an active and a passive joint at the ends. This replacement facilitates countering motion while preserving subsequent link orientations. Validation of kinematics is performed on palletizing manipulators from five different OEMs. The validation of Dobot Magician and ABB IRB1410 was carried out in real time and in their control software. Other robots from ABB, Yaskawa, Kuka and Fanuc were validated using control environments and simulators.

The proposed model enables the straightforward derivation of forward kinematics and transforms hybrid robots into equivalent serial-link robots. The model demonstrates high accuracy streamlining the derivation of kinematics.

The proposed model facilitates the use of classical methods like the Denavit–Hartenberg procedure with ease. It not only simplifies kinematics derivation but it also helps in robot control and motion planning within the workspace. The approach can also be implemented to simplify the parallelogram linkages of robots with higher degrees of freedom such as the IRB1410.

The tourism multiplier effect (TME) is the total economic impact of tourism demand, representing the linkages between tourism and other businesses in an area. However, study about it is limited in Indonesia, especially at the provincial level and after the COVID-19 crisis. This study aims to estimate the TME in all provinces of Indonesia, test its differences in priority and non-priority areas before and after the COVID-19 crisis, analyze its spatial distribution and examine the determinant factor of TME

This study applies an input-output model to measure the TME of all provinces in Indonesia, an independent sample t-test to examine the similarity of TME in priority and nonpriority areas, a paired sample t-test to examine the similarity of it before and after the COVID-19 crisis, and spatial analysis to check its spatial relationship.

The result shows that regional TME ranges from 1.25 to 2.05 in 2019, which changed slightly over time. The empirical result shows the TME difference before and after the COVID-19 crisis, and there is a spatial correlation in terms of TME with the hot spots are clustered in the eastern region of Indonesia, However, there was a slight change in the position of hot spots during the COVID-19 crisis. Moreover, the spatial model shows that value-added and employment in agriculture, manufacturing, trade and transportation affect the size of TME.

This study contributes to the academic literature by providing the first estimate of the TME at the provincial level in Indonesia, comparing the it in priority and non-priority areas before and after the COVID-19 crisis, and mapping its spatial distribution.

The purpose of this paper is to introduce a double-stator switched reluctance machine (DS-SRM) for electric vehicles (EVs) and to propose multi-mode operations for this machine.

Analysis of flux linkage distributions and torque characteristics using finite element method (FEM). Building a dynamic simulation model based on electromagnetic characteristics, mathematical equations and mechanical motion equations of the DS-SRM drive system. The paper proposes multi-mode operations (inner-stator excitation mode, outer-stator excitation mode and double-stator excitation mode) based on motor working regions. It also conducts simulation and experimental results to verify the effectiveness of the proposed multi-mode operations strategies and control schemes.

There is almost no electromagnetic coupling between the inner and outer stators due to the specially designed rotor structure and optimized windings polarity configuration. Analysis of flux linkage distributions and torque characteristics verified the independence of inner and outer stators. Proposal of multi-mode operations and corresponding control rules achieved the smooth switching between different modes.

The paper introduced the DS-SRM for EVs and proposed multi-mode operations, along with control rules, to optimize its performance. The specially designed rotor structure, optimized winding polarity configuration, and the proposed multi-mode operations contribute to the originality of the research.

This study aims to examine the impact of social media (SM) on the interactivity among teachers, among students and between students and teachers for sustainable academic performance and for achieving sustainable development (SD) in higher educational institutes. This study also investigates the moderating impact of knowledge creators (KNC) and knowledge seekers (KNS) on the collaborative learning environment using SM.

With the help of Vroom’s expectancy motivation theory (1964), collaborative learning theory and other theories, a theoretical model has been developed. This theoretical model has been tested using the structural equation modeling technique with 375 participants taken from different educational institutes. The respondent-–participants were both teachers and students.

The study found that SM plays a significant role in achieving SD al goals and enhances collaborative learning activities among teachers and students to improve academic performance to achieve SD in higher educational institutes. Also, the study highlighted that both “knowledge creators” and “knowledge seekers” have effective moderating impact on the linkage between “intention to use SM for knowledge sharing” and “collaborative learning using social media” to achieve SD al goals.

With the inputs from expectancy-instrumentality-valance theory and collaborative learning theory and existing literature, a theoretical model has been developed conceptually. Later, the model was successfully validated with an overall high explanatory power (72%) of this model. As the sample of the study do not represent a global representation of the population, thus the findings cannot be generalizable.

This study has provided valuable inputs to the SD practitioners and educational policymakers to formulate appropriate policies that enable SD al activities in higher educational institutes. This study also provides food for thought to the policymakers about the role of KNC and KNS toward the collaborative learning environment in achieving SD al goals in higher educational institutes.

The theoretical model developed in this study is unique. This study shows how both “knowledge creator” and “knowledge seeker” play a significant role toward collaborative learning and helps to achieve SD in higher learning institutes and improves their performance. The overall predictive power of the model is 72%, which also shows the effectiveness and uniqueness of the proposed model.

The study investigates the co-movements amongst real estate investments trust (REITs). This study examines the co-movements between the world and individual countries' REITs and the co-movements amongst country-pair REITs. This study explores the responsiveness of the REITs markets' co-movements to the 2008 global financial crisis (GFC), the coronavirus disease 2019 (COVID-19) pandemic and the Russian–Ukraine conflict.

The study employs a wavelet coherency technique and relies on data from six REITs markets over the 1995–2022 period.

The evidence shows a generally high level of coherency between the global and the country's REITs. The findings further indicate higher co-movements between some country pairs and a lower co-movement for others. The results suggest that the REITs markets increased in co-movements around the 2008 GFC, the COVID-19 pandemic and the Russian–Ukraine conflict. These increased co-movements mostly lasted for a short period suggesting REITs markets contagion around these global events. The results generally suggest interdependence between the global and the country's REITs. Additionally, interdependence is observed for some of the country-pair REITs.

The evidence indicates that REITs markets respond to global events. Thus, the increasing co-movement amongst REITs observed in this study may expose domestic REITs to global crisis. However, this study provides opportunities for minimising the cost of capital for real estate projects. Also, REITs provide limited diversification gains around crisis times. Therefore, countries need to open the REITs markets to global investors whilst pursuing policies to ensure the resilience of the REITs markets to global events. Investors should also take note of the declining geographic diversification gains from some country-pair REITs portfolios.

The study explores the barriers to ESG adoption and develops a hierarchical relationship between identified barriers to determine the driving and dependence power.

Through literature and unstructured interviews nine barriers affecting the adoption of ESG reporting were identified and examined using the modified Total Interpretive Structural Modelling (m-TISM) approach. Further, MICMAC analysis is used to analyse the driver-dependence power amongst the barriers.

In this analysis, the variable lying at the lowest level of hierarchy are considered to be the critical factor and lack of clarity around regulatory and reporting standards is found to be very critical for ESG adoption. To address impediments to ESG adoption, the government should make ESG disclosure mandatory and clearly explain the rules, regulations and advantages associated with ESG implementation.

The current study is very few among examining the barriers to ESG adoption and steppingstone towards the mandatory implementation of ESG disclosures in current scenario.

A nation's economic development is adversely affected by the rising population and the lack of employment opportunities, necessitating the promotion of entrepreneurial activities. This study aims to unfurl the critical factors shaping university students' entrepreneurial intentions (EI) in an emerging economy.

The study assessed the EI of 640 university students across India's top 5 central universities through structural equation modeling by extending the entrepreneurial event model (EEM) and dark triad theory. Mediation and moderation techniques were used to examine the model's direct and indirect linkages.

The results show that propensity to act (PTA), perceived resilience (PRS) and narcissism (NAR) magnify desirability, significantly increasing students' EI. The association between the underlying constructs is partially mediated by the PTA and perceived desirability (PD). In addition, the linkage between PD and students' EI is strengthened by the pursuit of excellence (PoE) and weakened by perceived risk (PR).

The study's findings could assist educators, universities, aspiring entrepreneurs, financial institutions, policymakers, investors, venture capitalists, incubators and accelerators in reinforcing entrepreneurial culture in India by establishing a link between crucial personality traits and intentions to start entrepreneurial ventures.

Personality traits such as NAR, resilience and the PoE have not received much attention in the entrepreneurship literature and call for a rigorous inquiry. The study tries to embrace these dominant personality traits by broadening the perspectives of EEM and dark triad theory via a comprehensive conceptual model. It also explores the role of the PoE and PR as moderators to examine the possible association between the identified constructs.

Driven by the dual-carbon target and the widespread digital transformation, leveraging digital technology (DT) to facilitate sustainable, green and high-quality development in heavy-polluting industries has emerged as a pivotal and timely research focus. However, existing studies diverge in their perspectives on whether DT’s impact on green innovation is synergistic or leads to a crowding-out effect. In pursuit of optimizing the synergy between DT and green innovation, this paper aims to investigate the mechanisms that can be harnessed to render DT a more constructive force in advancing green innovation.

Drawing from the theoretical framework of resource orchestration, the authors offer a comprehensive elucidation of how DT intricately influences the green innovation efficiency of enterprises. Given the intricate interplay within the synergistic relationship between DT and green innovation, the authors use the fuzzy-set qualitative comparative analysis method to explore diverse configurations of antecedent conditions leading to optimal solutions. This approach transcends conventional linear thinking to provide a more nuanced understanding of the complex dynamics involved.

The findings reveal that antecedent configurations fostering high green innovation efficiency actually differ across various stages. First, there are three distinct configuration patterns that can enhance the green technology research and development (R&D) efficiency of enterprises, namely, digitally driven resource integration (RI), digitally driven resource synergy (RSy) and high resource orchestration capability. Then, the authors also identify three configuration patterns that can bolster the high green achievement transfer efficiency of enterprises, including a digitally optimized resource portfolio, digitally driven RSy and efficient RI. The findings not only contribute to advancing the resource orchestration theory in the digital ecosystem but also provide empirical evidence and practical insights to support the sustainable development of green innovation.

The findings can offer valuable insights for enterprise managers, providing decision-making guidance on effectively harnessing the innovation-driven value of internal and external resources through resource restructuring, bundling and leveraging, whether with or without the support of DT.

The research findings contribute to heavy-polluting enterprises addressing the paradoxical tensions between digital transformation and resource constraints under environmental regulatory pressures. It aims to facilitate the simultaneous achievement of environmental and commercial success by enhancing their green innovation capabilities, ultimately leading to sustainability across profit and the environment.

Compared with previous literature, this research introduces a distinctive theoretical perspective, the resource orchestration view, to shed light on the paradoxical relationship on resource-occupancy between DT application and green innovation. It unveils the “black box” of how digitalization impacts green innovation efficiency from a more dynamic resource-based perspective. While most studies regard green innovation activities as a whole, this study delves into the impact of digitalization on green innovation within the distinct realms of green technology R&D and green achievement transfer, taking into account a two-stage value chain perspective. Finally, in contrast to previous literature that predominantly analyzes influence mechanisms through linear impact, the authors use configuration analysis to intricately unravel the complex influences arising from various combinatorial relationships of digitalization and resource orchestration behaviors on green innovation efficiency.