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This paper aims to propose a structured model based on a data mining algorithm that can calculate, based on business association (BA) attributes, the probability of micro and small enterprises (MSEs) becoming a new member of a BA. Another goal is the probability of a BA attracting new members.

As a methodological procedure, the authors used the Naive Bayes data mining algorithm. The collected data were analyzed both quantitatively and qualitatively and then used to define the model, which was tested randomly, while allowing for the possibility of future validation.

The findings suggest a structured model based on a data mining algorithm. The model can certainly be used as a management tool for BAs concentrating their efforts on those businesses that are certainly potential new recruits. Further, for an MSE, it serves as a means of evaluating a BA, indicating the possible advantages in becoming a member of a particular association.

This paper is not intended to be generalized, considering that it only analyzes the BAs of Rio Grande do Sul, Brazil. In this way, when applying this model to other situations, the attributes listed here can be revised and even modified to adapt to the situation in focus.

The use of the proposed model will make it possible to optimize the time of BA managers. It also gives MSE greater reliability in choosing BA.

Using this model will provide better decision-making and better targeting, thus benefiting both the BAs and the MSEs, which can improve their management and keep jobs.

This paper contributes to the literature because it is the first to connect BAs, MSEs and Naive Bayes. Also, this study helps in better management for BA managers in their daily activities and provides a better choice of BA for MSE managers. Also, this study contextualizes BAs, MSEs and data mining in an objective way.

Purpose — In this chapter, we will review several alternative methods of collecting data from mobile phones for human mobility analysis. We propose considering cellular network location data as a useful complementary source for human mobility research and provide case studies to illustrate the advantages and disadvantages of each method.

Methodology/approach — We briefly describe cellular phone network architecture and the location data it can provide, and discuss two types of data collection: active and passive localization. Active localization is something like a personal travel diary. It provides a tool for recording positioning data on a survey sample over a long period of time. Passive localization, on the other hand, is based on phone network data that are automatically recorded for technical or billing purposes. It offers the advantage of access to very large user populations for mobility flow analysis of a broad area.

Findings — We review several alternative methods of collecting data from mobile phone for human mobility analysis to show that cellular network data, although limited in terms of location precision and recording frequency, offer two major advantages for studying human mobility. First, very large user samples – covering broad geographical areas – can be followed over a long period of time. Second, this type of data allows researchers to choose a specific data collection methodology (active or passive), depending on the objectives of their study. The big mobile phone localization datasets have provided a new impulse for the interdisciplinary research in human mobility.

Originality/value of chapter — We propose considering cellular network location data as a useful complementary source for transportation research and provide case studies to illustrate the advantages and disadvantages of each proposed method. Mobile phones have become a kind of “personal sensor” offering an ever-increasing amount of location data on mobile phone users over long time periods. These data can thus provide a framework for a comprehensive and longitudinal study of temporal dynamics, and can be used to capture ephemeral events and fluctuations in day-to-day mobility behavior offering powerful tools to transportation research, urban planning, or even real-time city monitoring.

This study aims to develop conceptual arguments about intrapreneurship relative to role theory.

The challenge to the intrapreneurship concept is that no single or combination of personality traits, individual characteristics or attitudes can fulfill the causes of the phenomenon, as these factors are context-bound. One explanation for individual- and macro-level contrasting outcomes is the diverging effect of expectations. The structural and interactionist perspective of sociology is used to understand the intrapreneurship concept because intrapreneurs live within a society and shape their course per the expectations of others.

Intrapreneurs have been trying to infer about what is seen as crucial individually related to interactions within the existing context; more importantly, acting in an intrapreneurship role can be defined and learned by expectations.

With the convenient expectations from other members, families or environments, organization members will value the innovation and self-direction of intrapreneurship more highly that such a taste for an acting role may be an important factor in the decision to become an intrapreneur.

To the best of the authors’ knowledge, the paper emphasized for the first time that the consequences of exposure to social expectations for the development of intrapreneur roles, particularly the broad portfolios of skills and motivation, are relevant to intrapreneurship. Previous approaches depend on individuals, organizations or the environment to have different approaches to likely employees to be intrapreneurs. The paper first argues that context is important for understanding how and why context can be linked to individual intrapreneurs and how intrapreneurship can be defined as roles rather than a task or unique potential entrepreneurs.

International trade and its effects on the environment are increasingly discussed both in academia and by policymakers. To counter negative effects of international trade on the environment, so called environmental provisions have been integrated in trade agreements aimed at businesses and economies. However, as both the intent and effectiveness of these provisions are controversial, this paper aims to provide an overview of the current state of research and identified key factors influencing their effectiveness.

The authors conduct a systematic literature review of 44 papers on the effects of environmental provisions in international trade agreements on the environmental performance of businesses, as well as economies from 1992 to mid-2024.

The integration of environmental provisions into trade agreements generally has positive effects on the environment while their effectiveness is influenced by their design and several boundary conditions. Alongside the importance of effective enforcement mechanisms, reputation concerns of businesses and lobbyism are discussed as intermediary factors in the design and impact of environmental provisions.

The insights can benefit policymakers to optimize future environmental provisions and advance the effectiveness of policies aimed at balancing the effects of trade liberalization with environmental protection.

Social sustainability is increasingly relevant for creating more sustainable trade policy while societal mechanisms seem to be an adequate tool to ensure effective enforcement of ecological provisions.

To the best of the authors’ knowledge, this review is the first of its kind to provide a systematic overview of the literature on the effectiveness of environmental provisions that combines the micro-level of businesses and macro-level of economies, although the importance for trade in general and environmental protection, in particular, has been recognized in the academic literature.

This paper evaluates the factors that help in enabling the intrapreneurial behaviour amongst the employees according to their importance. This study will evaluate the relationship between these factors and intrapreneurship. It will also provide a significant contribution in understanding what it takes to be among India's best companies.

This study incorporates a quantitative approach where the data has been collected through the “Great Place to Work” Institute's list of top companies in India to work for. The final sample included 109 employees from 50 companies. Correlation and regression analyses are used for data analysis.

The results indicated that there is a positive and significant effect of the environment and organizational factors on intrapreneurship. Within the individual factors, management support in organizational factors and technological opportunities present in the market (environmental factors) are perceived as the most important factors for intrapreneurial activities. Additionally, “self-renewal activities” are considered as an important intrapreneurial activity for the respondents.

The results of this study are significant because the sample is taken of the companies already known for their workplace culture. This helped in cross-validating the results.