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This chapter aims to estimate the impact of the use of an innovative cultivation method on the social, economic and environmental aspects in the French region Aix-en-Provence, by using the survey data for 200 heterogeneous vegetable producers (organic and conventional). It distinguishes three types of producers in the French region Aix-en-Provence. First, conventional producers (n = 100) who used a high level of mechanization, better access to water, high yield, high labor costs. Second, certified organic producers (n = 70) who used organic technologies such as biotechnology and rotation, low yield, high organic product price compared to conventional products, a family workforce and high transport. Third, noncertified organic producers (n = 30) have used the same technologies as certified organic producers, while they sell their products at the same price as conventional products. Labor is the member of the family. These noncertified farms are marked by high operating and transport costs and low yield compared to conventional producers or certified organic producers. The results show that this cultivation method has a positive effect on the environmental aspect, however a negative one on the social and economic aspect.

The study aims to develop a model that supports the application of data science techniques for real estate professionals in the fourth industrial revolution (4IR) era. The present 4IR era gave birth to big data sets and is beyond real estate professionals' analysis techniques. This has led to a situation where most real estate professionals rely on their intuition while neglecting a rigorous analysis for real estate investment appraisals. The heavy reliance on their intuition has been responsible for the under-performance of real estate investment, especially in Africa.

This study utilised a survey questionnaire to randomly source data from real estate professionals. The questionnaire was analysed using a combination of Statistical package for social science (SPSS) V24 and Analysis of a Moment Structures (AMOS) graphics V27 software. Exploratory factor analysis was employed to break down the variables (drivers) into meaningful dimensions helpful in developing the conceptual framework. The framework was validated using covariance-based structural equation modelling. The model was validated using fit indices like discriminant validity, standardised root mean square (SRMR), comparative fit index (CFI), Normed Fit Index (NFI), etc.

The model revealed that an inclusive educational system, decentralised real estate market and data management system are the major drivers for applying data science techniques to real estate professionals. Also, real estate professionals' application of the drivers will guarantee an effective data analysis of real estate investments.

Numerous studies have clamoured for adopting data science techniques for real estate professionals. There is a lack of studies on the drivers that will guarantee the successful adoption of data science techniques. A modern form of data analysis for real estate professionals was also proposed in the study.

In a dual-robot system, the relative position error is a superposition of errors from each mono-robot, resulting in deteriorated coordination accuracy. This study aims to enhance relative accuracy of the dual-robot system through direct compensation of relative errors. To achieve this, a novel calibration-driven transfer learning method is proposed for relative error prediction in dual-robot systems.

A novel local product of exponential (POE) model with minimal parameters is proposed for error modeling. And a two-step method is presented to identify both geometric and nongeometric parameters for the mono-robots. Using the identified parameters, two calibrated models are established and combined as one dual-robot model, generating error data between the nominal and calibrated models’ outputs. Subsequently, the calibration-driven transfer, involving pretraining a neural network with sufficient generated error data and fine-tuning with a small measured data set, is introduced, enabling knowledge transfer and thereby obtaining a high-precision relative error predictor.

Experimental validation is conducted, and the results demonstrate that the proposed method has reduced the maximum and average relative errors by 45.1% and 30.6% compared with the calibrated model, yielding the values of 0.594 mm and 0.255 mm, respectively.

First, the proposed calibration-driven transfer method innovatively adopts the calibrated model as a data generator to address the issue of real data scarcity. It achieves high-accuracy relative error prediction with only a small measured data set, significantly enhancing error compensation efficiency. Second, the proposed local POE model achieves model minimality without the need for complex redundant parameter partitioning operations, ensuring stability and robustness in parameter identification.

Work environments are undergoing a transition and COVID-19 accelerated this change. Prior studies have associated various physical, digital and social work environment elements with occupational well-being. However, holistic approaches to the social work environment to compare the effects of the different elements have received less attention. The purpose of this study is to examine the relationship of various social work environment elements with hybrid worker well-being. The findings help organizations design their work environments and cultures for the post-COVID era.

The study builds on a quantitative survey with 1,057 respondents. The respondents were randomly selected, the answers were anonymous and the results were based on regression analysis.

The analysis indicated that working methods and practices, leadership and management practices, organizational communality and social interaction associate with hybrid worker well-being. Organizational values, reward systems and organizational structures yield no association with hybrid worker well-being.

The value of this paper is in that it investigates elements of the social work environment, presents a research model that examines the relationship of social work environment elements with hybrid worker well-being and provides new empirical data on their implications in a comparative manner.

The purpose of the article is to identify relevant criteria for decision support in the implementation of waste-to-energy (WtE)-based systems.

The methodology is a simple case study with a qualitative approach. Five experts involved in the project of a thermoelectric power plant qualitatively evaluated, on a Likert scale, a decision model with 15 indicators derived from recent studies. The research object was the first stage of a project to implement a thermoelectric plant employing municipal solid waste (MSW) in southern Brazil.

The study identified 15 criteria supporting the decision-making process regarding WtE implementation for MSW in a mid-sized city in southern Brazil. The study identified that compliance with MSW legislation, compliance with energy legislation, initial investment and public health impact are the most influential criteria. The study offered two models for decision processes: a simplified one and a complete one, with ten and fifteen indicators, respectively.

The study concerns mid-sized municipalities in southern Brazil.

Municipal public managers have now a methodology based on qualitative evaluation that admits multiple perspectives, such as technical, economic, environmental and social, to support decision-making processes on WtE technologies for MSW.

MSW management initiatives can yield jobs and revenues for vulnerable populations and provide a correct destination for MSW, mainly in developing countries.

The main originality is that now municipal public decision-makers have a structured model based on four constructs (technical, economic, environmental and social) deployed in 15 indicators to support decision-making processes involving WtE and MSW management.

This study aims to investigate the consumer behavior toward telemedicine services in India during the COVID-19 pandemic onset. With lockdown restrictions and safety concerns in visiting brick-and-mortar clinics or hospitals during the pandemic, Telemedicine had emerged as a potent alternative for seeking redressal to health issues. Based on theory and focus interviews with the telemedicine users, the researchers proposed a model to understand the intent and actual usage of telemedicine in India.

The cross-sectional study undertaken used a questionnaire designed on a seven-point Likert scale and administered to respondents with the objective of identifying the determinants of intent and actual usage of telemedicine services. Simple random sampling was used to collect primary data. The data was cleaned and finally a sample of 405 responses complete in all respects was considered for analysis. The questionnaire comprised of 34 items and following the recommendation of Hair et al. (2016), which says the minimum sample size in structural equation modeling should be ten times the number of indicator variables, a sample size of 405 was deemed adequate.

The research paper finds that performance expectancy, attitude, credibility and self-efficacy positively impact the intention of consumers to use telemedicine services. As the effort expectancy or risk perception toward telemedicine increases the intent and actual usage of telemedicine decreases. The intention to use telemedicine emerged as a strong predictor of the actual usage of telemedicine. Intent to use telemedicine was explained 81.4% by its predictors of performance expectancy, effort expectancy, attitude, risk, credibility and self-efficacy, and actual usage was explained 79.9% by its predictors. This study also reports that telemedicine was found to be popular among chronic as well as episodic patients though the preference was skewed in favor of the episodic patients. One of the advantages of telemedicine is its availability round the clock, and the study found that 8 a. m. to 12 noon time slot as the most preferred slot for seeking telemedicine services.

Chang (2004) opined that telemedicine can fulfill the needs of all stakeholders: citizens, health-care consumers, medical doctors and health-care professionals, policymakers, and so on. Considering the promise telemedicine holds, this realm must be studied and leveraged to the full potential. The study found that patients were using telemedicine even for their day-to-day aliments. This indicates a growing popularity of telemedicine and as such an opportunity for telemedicine companies to leverage it. In India, pharmaceutical companies cannot give commercial advertisements for medicines, and the same can only be sold through a registered medical practitioner’s prescription. As such there is total dependency on the medical practitioner for the sale of medicines. Telemedicine companies offer services of home delivering medicines clubbed with medical consultation thus giving them forward integration in their business models. Using telemedicine the patients had control over the timings of the services offered, and as such the waiting time to get a consultation and subsequent treatment was reduced considerably. Best medical advice from across the globe is available to the patient at less cost. Medical practitioners also stand to benefit as they can treat a variety of cases, collaborate among the medical fraternity and give consultation safely in case of fatal contagious diseases.

This study points to a definite growing popularity of telemedicine services not only in episodic patients but also chronic patients. Telemedicine with its unique advantages holds the promise to grow exponentially in the future and is a compelling health-care segment to focus on for delivering health-care solution to the geographically distant consumers.

The purpose of this study was to develop and validate a scale to assess the influence of Higher Educational Facilities for the growth of education in higher education institutions.

The first step in the process of scale development is to generate an item pool containing as many items as possible which captures the construct of interest. A total of 111 items were constructed for the initial try-out of the scale measuring the construct of higher educational facilities. This rating scale was based on the Likert-type was designed, where each item had to be rated on a five-point scale. The scale consisted of a few items involving the dimensions of infrastructure, quality assessment and quality assurance regard to the vision actualization.

Higher Educational Facilities Scale (HEFS) was developed by the investigator and designed in the format of a 5-point rating scale of the Likert type. There are different phases identified for the scale construction. In the first phase, items are created and the content’s validity is determined. The scale is constructed in the second phase. Pre-testing the questions, administering the survey, reducing the number of items and determining how many factors the scale captures are all steps in the scale construction process. The number of dimensions, reliability and validity are all verified in the third phase, scale evaluation. In developing the scale, the content and face validity was ascertained. The reliability of the scale and its three subscales were established. This scale has potential value for policymakers to assess the perception held by the religious faculty members working in higher education institutions.

The research is part of the doctoral thesis by Dr Deepa Thomas under the supervision of Dr Fr. Joseph C. C. and the co-supervision of Dr Kennedy Andrew Thomas. The purpose of the scale is to assess the higher educational facilities of in institutions of higher Education. Quality, excellence and service are the vision and purpose of higher education institutions to provide ample opportunities and good facilities for their beneficiaries, thus creating tremendous changes in the Indian education scenario.

High levels of interior water vapour lead to condensation and black mould that in turn represent significant risks to residential properties and their occupants. Beliefs about window opening are good predictors of the degree to which householders will actually open windows to purge their homes of water vapour, including water vapour that they themselves generate. The present study tested if a short information-giving intervention could enhance householders’ beliefs that foster window opening as purge ventilation and, in turn, lead to greater window opening.

Data were collected from 242 UK householders with robust psychometrically sound measures embedded in an online self-report survey that also presented the intervention information.

The intervention led participants, and males in particular, to have significantly greater concerns about condensation and mould and significantly less concerns about heat loss costs arising from opening windows, and these altered beliefs in turn predicted a greater intention to open windows in the future.

By sharing simple information, surveyors and other building professionals can help householders take the simple step of opening their windows and so reduce the threats that condensation and mould present to themselves and their homes.

This is the first study to test (1) a time-based model that predicted the intervention would have a positive effect on specific window opening attitudes and that those new attitudes would in turn affect window opening intentions, and (2) if the intervention had different effects on men and women.

This study addresses the empirical results of the spillover effect with export as the primary economic activity that enhances local businesses' total factor productivity (TFP). A learning mechanism is expected to be generated and used as the basis for the policy implication.

This study adopted the Cobb–Douglas function and multiple estimation approaches, including the generalized method of moments, the Olley–Pakes and the Levinsohn–Petrin estimation techniques. The findings were estimated based on the panel data of a Vietnamese local businesses survey conducted by the General Statistics Office of Vietnam (GSO) from 2010 to 2019.

The results showed that the highest TFP belongs to the businesses in the Southeast region, the Mekong Delta region, the mining industry and the foreign-invested enterprises. The lowest impacted TFP are businesses in the Northwest region and agricultural, forestry and fishery sectors. In addition, the estimated results also show that the positive spillover effect on TFP is shown through forward and backward linkage. The negative spillover effect is expressed through the backward and horizontal channels.

This study offers original empirical evidence on the learning mechanisms via which exports contribute to productivity improvement in a developing Asian economy, so making a valuable contribution to the existing academic literature in this domain. The findings of this research make a valuable contribution to the advancement of understanding on the many ways via which spillover effects manifest such as horizontal, forward, backward and supplied-backward linkage.

The study's findings indicate that it is advisable for governments to give priority to the development and improvement of forward and supply chain linkages between exporters and local suppliers. This approach is recommended in order to optimize the advantages derived from export spillovers. At the organizational level, it is imperative for enterprises to strengthen their technological and managerial skills in order to efficiently incorporate knowledge spillovers that originate from overseas partners and trade counterparts.

This study sheds new evidence on the export spillover effect on productivity in emerging economies, with Vietnam as the case study. The paper contributes to the research's originality by adopting novel methodological aspects to estimate local businesses' impact on total factor productivity.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0373

This study aims to investigate the relationship between strategy intent (product-service innovation intention) and outcome (product-service innovation outcome), and the role that external sources of innovation play in influencing this relationship.

Using data obtained from the community innovation survey, we apply a logit regression to a sample of 1,419 Portuguese firms. By examining the moderating effect of open innovation breadth, we assess how the relationship between differentiation intent and outcome is contingent upon the involvement of external stakeholders.

Our findings reveal that the relationship between differentiation intent and outcome is contingent upon the moderating effect of open innovation breadth. Our analysis suggests that the negative influence of different sources of innovation can be addressed by adopting a paradox lens.

This research provides valuable insights for managers. By simultaneously pursuing a differentiation strategy and engaging in collaboration with external sources, firms may compromise their ability to effectively differentiate their offer. Managers should consider the potential tensions arising from internal and external stakeholder relationships to optimize their innovation strategies.

This study contributes to the existing literature by shedding light on the role of external innovation sources in influencing the relationship between differentiation intent and outcome and the importance that information systems may have in this relationship. By exploring the moderating effect of open innovation breadth, we provide a nuanced understanding of how firms can navigate organizational tensions and leverage innovation for competitive advantage.