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Recent years have produced significant demand for geographical contributions to the study of social movements in general and of environmental social movement organizations (ESMOs) in particular. Geographical approaches to the study of ESMOs emphasize “the mediation of social movement agency by place” (Miller, 2000; Routledge, 1993) and call attention to the role of place-based environmental knowledge (EK) in the broader “struggle(s) over meaning” that increasingly constitute environmental politics (Buechler, 1997; Escobar, 1992; Rangan, 2000; Watts, 1990). My chapter responds to this call by providing an examination of the reproduction of EK by antipollution organizations in India’s central Ganges River Basin (GRB). Through interviews with organization leaders and members, along with analysis of organizational websites and publications, I examine the EK of two key antipollution organizations in the GRB: The Sankat Mochan Foundation (SMF) and Kanpur Eco-Friends (KEF). Analysis focuses on methods of knowledge reproduction employed by each organization, their respective framing practices, and the localized natures of the EK they reproduce. I argue that each organization works to reproduce a specific and place-based understanding of pollution in the GRB that informs their framing of the pollution problem, the tactical activities in which their members engage, and the power relations that exist between the two organizations and their leaders. Further, I argue that engaging with EK as both a method of understanding pollution and a tactic for consolidating political power is essential to making sense of the relative success of these movement organizations and the challenges they face in trying to build a broader coalition and mass-mobilization against pollution in the Ganges.

This study aims to examine the impact of the servitization on the performance of small and medium enterprises (SMEs) in Brazil.

The study uses data from Brazilian SMEs and applies partial least squares structural equation modeling (PLS-SEM) to test the research hypotheses.

The findings suggest a positive relationship between servitization and SME performance. It is found that the strategy of offering base services does impact SME performance. Furthermore, servitization aims to promote a fit between environmental pressures and SME performance.

SMEs can use servitization to increase their performance in spite of their resources restrictions, size limitation and low level of service revenue. However, the adoption of servitization should be accompanied by managerial adjustments in servitization practices.

This paper is dedicated to investigating the servitization-performance relationship in the context of SMEs, which is not a usual research publication. Moreover, it adds to the servitization theory by demonstrating that it is not necessary to reach a critical mass of services to be profitable and base services may be also a source of revenues and profits.

This study aims to examine the determinants of consumer behavioral intention to use the restaurant, concert and education services online during and after the COVID-19 pandemic.

A conceptual model based on the Unified Theory of Acceptance and Use of Technology (UTAUT) was tested via structural equation modeling by using data collected from a sample of 420 Brazilian consumers.

The results showed that performance expectancy and social influence are the most critical determinants of consumer behavioral intention to use services online during the pandemic. The results also provided evidence that the pandemic has generated significant impacts on future consumer behavior.

This study contributes in a multidisciplinary way to the literature on hospitality, entertainment and education services, by applying the UTAUT theory and testing the model during and after the COVID-19 pandemic context. Moreover, this study provides empirical evidence from Brazil, one of the most affected countries by COVID-19.

This study aimed to find factors influencing the acceptance of telemedicine for adults in Brazil. Moreover, it investigates the moderating role of disease complexity and the generational digital divide phenomenon on the intention to use the telemedicine service.

A quasi-experiment was employed. Primary data were collected using a survey research method considering two different scenarios based on disease complexity and symptom severity. A total of 248 responses were collected using a structured questionnaire. The authors also tested these two scenarios in three generations (X, Y and Z) of adults. Partial least squares structural equation modeling (PLS-SEM) was used to analyze the collected data and test the research hypotheses.

The results indicated that performance expectancy and perceived security and reliability are two predictors of the behavioral intention to use telemedicine, whereas effort expectancy and social influence showed no statistical significance. Furthermore, the results demonstrated that adults tend to adopt telemedicine regardless of the level of disease complexity. Finally, this study does not support the existence of a digital divide in the three generations.

The study applies the UTAUT model to assess the telemedicine acceptance for younger generations. It examines patient risk perception (security and reliability) as one antecedent of telemedicine acceptance.

The purpose of this paper is to propose an optimal predictive model for the short-term forecast of real-time non-stationary machine variables by combining time series prediction with adaptive algorithms to minimize the error and to improve the prediction accuracy.

The proposed model is applied for prediction of speed and controller set point of three-phase induction motor operating on closed loop speed control with AC drive and PI controller. At Stage 1, the trend of the machine variables has been extracted and added to auto-regressive moving average (ARMA) time series prediction. ARMA prediction has been carried out using different combinations of AR and MA methods in order to make prediction with less Mean Squared Error (MSE).

The prediction error indicates the inadequacy of the model to estimate the data characteristics, which has been resolved at the subsequent stage by cascading an adaptive least mean square finite impulse response filter to the time series model. The adaptive filter receives the predicted output including training data and iteratively adjusts its coefficients for zero error convergence.

The componentized data prediction based on time series and cascade adaptive filter algorithm decomposes the non-stationary data characteristics for predictive maintenance. Evaluation of the model with different combination of time series algorithms and parameter settings of adaptive filter has been carried out to illustrate the performance of the prediction model. This prediction accuracy is compared with existing linear adaptive filter prediction using MSE as comparison index. The wide margin in the MSE values substantiates the prediction efficiency of the proposed model for machine data.

This model predicts the dynamic machine data with component decomposition at high accuracy, which enables to interpret the system response under dynamic conditions efficiently.

This chapter looks at how sensitivity to event design and the creative process for an arts event also can have an impact on its ongoing management and tourist experience, by applying a new assessment tool, sustainable creative advantage (SCA), to gauge its performance.

A case study approach was used to assess SCA for the Sculpture by Sea, Bondi, Sydney 2015, in order to discuss how its management enables satisfying arts leisure experiences. Two key activities in the research were (1) in-depth interviews with organizers, full and volunteer staff, artists, gallery owners, and participants and (2) participant observation of touristic performances and other forms of engagement with the sculptures.

In its 19th edition, the event could still be considered a fresh and inspiring experience for tourists. However, crowding on weekends can affect the experience for all participants. Tactile tours are a unique feature of the event and could be promoted more to tourists, particularly the disabled.

Applying SCA needs careful timing, in order to collect information when interviewees are available and the event itself is running. Approaches should be made to organizers before, during, and after the event for information.

Event organizers could use SCA to understand more about controlling tourist experiences and how creative management and marketing of an event can have an impact on overall participant satisfaction.

Could also offer insights to academics studying glocality and events, the relationship of curatorial power to content/experience, or how such events can add to the study of leisurescapes in cultural tourism.

The purpose of this paper is to examine new product development (NPD) financial performance enablers through examining the roles of NPD capabilities improvement, NPD knowledge sharing and NPD internal learning in manufacturing organisations in Jordan.

Based on relevant literature review on NPD performance, a structured questionnaire was developed to collect data related to NPD performance measures. Questionnaires were distributed to a sample of 558 manufacturing organisations in Jordan, out of which 355 were returned and valid for the analysis. Exploratory and confirmatory factor analyses were applied to reveal NPD performance success dimensions that manufacturing organisations use to assess NPD performance success. Then, path analysis was employed to examine the research model and test its hypotheses.

The study’s findings reveal that manufacturing organisations use a multidimensional construct for assessing NPD performance success, which consists of NPD financial performance, NPD internal learning, NPD capabilities improvement, NPD knowledge sharing, and NPD marketing performance. NPD capabilities improvement exerted a positive and significant effect on each of NPD internal learning, NPD knowledge sharing, and NPD marketing performance, respectively. NPD knowledge sharing exerted a positive and significant effect on each of NPD internal learning NPD marketing performance. Each of NPD internal learning and NPD marketing performance exerted a positive and significant effect on NPD financial performance. The structural findings also indicate that 38.1 per cent (R2 is 0.381) of NPD financial performance is explained by the path of NPD capabilities improvement, NPD knowledge sharing and NPD marketing performance, which is the strongest path in the empirical model.

The paper’s focus on manufacturing organisations limits its contribution to the manufacturing sector only. The services sector is a rich field for understanding NPD financial performance enablers in various service industries. Further, the paper focusses on only five dimensions of NPD performance success, other dimensions of NPD performance success might add more insights to their effect on NPD performance success measures especially their effect on organisational performance.

The findings of this study provide managers of manufacturing organisations with empirical insights related to the multidimensionality of NPD and their complex relationships to enhance NPD financial performance. The empirical findings assist managers to assess their NPD strategies, processes and implementation based on a results-oriented approach. The major contribution of the study is identifying the strongest paths of NPD financial performance enablers which reveals the complexity and criticality of NPD capabilities improvement, NPD knowledge sharing and NPD marketing performance on NPD financial performance. The rationale is NPD financial performance is still the most important NPD performance success dimension amongst manufacturing organisations.

The originality of this paper stems from developing and testing a multidimensional model of NPD financial performance enablers for the first time in emerging markets, Jordan. NPD financial performance is a function of other areas of NPD performance dimensions, namely; NPD capabilities improvement, NPD knowledge sharing and NPD marketing performance. This empirical evidence is provided to managers for the first time by this study.

Mergers and acquisitions (M&) are increasingly becoming a strategy of choice for companies attempting to achieve and sustain competitive advantage. However, not all M&As are a success. In this paper, we examine the three main reasons highlighted in the literature as major causes of M&A failure (clashing corporate cultures, absence of clear communication, and employee involvement) in three Indian pharmaceutical companies, and we analyze the role played by the HR function in addressing them. Also, we discuss the importance of gaining the commitment and focus of the workforce during the acquisition process through employee involvement.

The topic of Lean Six Sigma (LSS) implementation in a supply chain context is an emerging research stream comprising of diverse objectives and complex processes thereby presenting opportunities for further exploration and organizational process improvement. Thus, this study proposes an integrated multi-criteria decision-making methodology to determine what can facilitate the successful implementation of LSS as an organizational change strategy in the manufacturing supply chain.

The proposed methodology based on Decision-Making Trial and Evaluation Laboratory and hierarchical Evaluation Based on Distance to Average Solution is employed to ascertain the relative importance and priorities of an identified framework of factors with the aid of opinions of managers in the Nigerian plastics industry.

The results show a high significance of institution-based factors (e.g. government regulations) and present relevant implications to the policymakers as well as the managers and practitioners of the plastics manufacturing industry.

This study indicates a possible pathway to accurately evaluate a framework of critical factors to integrate and institutionalize LSS in the manufacturing supply chain for organizational performance improvement.