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On its way to develop a smart grid in Indonesia, one key enabler in the early stage of implementation is advanced metering infrastructure (AMI). Thus, Perusahaan Listrik Negara (PLN), an electrical energy utility company owned by the government of the Republic of Indonesia as the only electricity utility company servicing customers from upstream to downstream in Indonesia, has started AMI program at some main cities. With AMI, real-time energy consumption profile, energy meter status and condition, and customer power quality can be acquired. Subsequently, these data collected by AMI can be used for further smart grid implementation by such IT systems and big data analysis. Instead of its function for smart grid backbone, AMI also significantly support smart energy on the city as a part of smart city initiatives. Nevertheless, its implementation requires more investment than the conventional metering system. This investment needs to be evaluated to define whether AMI is feasible and viable or not. This chapter is intended to observe the feasibility of AMI implementation in Indonesia using cost-benefit analysis (CBA). Two schemes were used as study objects, one scheme in which the communication infrastructure was managed by PLN itself, and the other one in which the communication infrastructure was managed by a third party. From the analysis, it appears that both schemes are proven to be feasible.

Neuromarketing is a marketing communication field that applies neuroscience and physiological research tools to study consumer behavior toward stimuli, viz., ads and brands. This study aims to assess research trends in the neuromarketing field on the most influential journals, authorships, countries, citations and co-occurrences. The Scopus database is used to analyze identified articles from 2013 to 2022 and for the eligible research articles, a “systematic methodological review” (SMR) on consumer behavior through neuromarketing approach was done. “Visualization of Science (VOS)” viewer and “Biblioshiny” by R-studio software have been used for mapping the keyword analysis, co-citation analysis and author occurrence analysis. It was further found that of the top 10 academic institutions, the list is dominated by the six Asian institutions. It was further witnessed that journal “Physiology and Behavior” is trending as the most dedicated and emerging journals on neuromarketing and consumer behavior. Asian nations such as Bangladesh, China, India, Indonesia, etc., are turning out to be an emerging collaborators and publishers in this niche area of research, thereby giving tough competition to most developed countries. The findings of the thematic mapping show that neuromarketing is itself a very novel and newest area of study and topics such as “human marketing,” “neuromarketing,” “consumer behavior” and “electroencephalography” are new dimensions that can be looked upon in future.

The Chinese housing market has witnessed rapid growth during the past decade and the significance of housing price forecasting has undoubtedly elevated, becoming an important issue to investors and policymakers. This study aims to examine neural networks (NNs) for office property price index forecasting from 10 major Chinese cities for July 2005–April 2021.

The authors aim at building simple and accurate NNs to contribute to pure technical forecasts of the Chinese office property market. To facilitate the analysis, the authors explore different model settings over algorithms, delays, hidden neurons and data-spitting ratios.

The authors reach a simple NN with three delays and three hidden neurons, which leads to stable performance of about 1.45% average relative root mean square error across the 10 cities for the training, validation and testing phases.

The results could be used on a standalone basis or combined with fundamental forecasts to form perspectives of office property price trends and conduct policy analysis.

This study aims to examine the impact of migration growth on environmental outcomes and local governance and assess how well the existing local municipal governance has responded to the environmental impact of increased migration influx in Ontario, Canada using the annual data during 2012–2021.

This study used the grey relational analysis (GRA) to examine the correlation degree between migrant growth, environmental outcomes and local governance, used coupling coordination degree model (CCDM) to access to what extent the existing local governance systems have responded to the environmental impact of immigrant growth.

Results show that higher immigrant populations are associated with worse environmental outcomes and the need for more municipal environmental investment and service. The present local municipal environmental service in Ontario lags behind in response to the environmental impacts of increased migration. Good local governance practices and environmental services are required to improve the environmental adaptation capacity of host countries to migrant influx.

Climate change has been regarded as an important driver of internal and international human migration. The mass influxes of migrants will threaten cities’ environmental quality and put considerable pressure on municipal services. This study provides empirical evidence for Ontario’s municipal environmental governance and relevant authorities on how to deal with the environmental impact of increased migration and contributes to call the attention of other countries to the urban environmental pressure caused by migration influx due to the changing climate world wide.

This study examines how informal business networks achieve marketing goals in socially uncertain contexts. Drawing from multiple historical sources, Shangbangs, a type of business network that thrived in pre-1949 China, are analyzed.

The Critical Historical Research Method (CHRM) undergirds a study of Shangbangs’ historicity (i.e. their socio-historically embedded multiplicity, including organizational forms, activities and connotations.

As informal regional, professional, project-based, special-product-based or mixed marketing networks, Shangbangs relied on “flexible specialization” and coupled multiple business needs to market goods and services, business organizations, specific social values and, when necessary, to debrand business rivals.

This analysis extends theories about marketing networks by probing their subtypes, diverse marketing activities, multipronged channels and relationship building with social entities (including underground societies, business associations and guilds) in response to pre-1949 China’s market uncertainties. Substantiating an alternative approach to “flexible specialization” and marketing innovations within the pre-1949 Chinese economy shows how a parallel theoretical framework can complement western-based marketing theories.

This first comprehensive analysis of Shangbangs, an innovative historical Chinese marketing network outside the conventional market-corporate dichotomy, can inform theory building for marketing strategy-making and management conditioned by social contexts.

The purpose of this paper is to empirically analyze the impact of chief executive officer (CEO) turnover on strategic change and explore the mediating role of organizational slack between them, as well as the moderating role and joint moderating role of top management team (TMT) external social network, ownership nature and industry type.

Based on the upper echelons theory, resource allocation theory and structuration theory, this paper takes the unbalanced panel data of A-share listed companies in Shanghai and Shenzhen Stock Exchanges of China from 2001 to 2018 as the research sample, uses ordinary least squares (OLS) regression method and fixed effect model to study the relationship between CEO turnover and strategic change, and focuses on the mediating mechanism and moderating mechanism between them.

The authors find that CEO turnover is positively related to strategic change. When a CEO turns over, a new CEO will initiate strategic change. Precipitation organizational slack plays a mediating role between CEO turnover and strategic change. Non-precipitation organizational slack has no mediating effect between CEO turnover and strategic change, which is embodied as “suppressing effects.” When the non-precipitation organizational slack variable is controlled, the impact of CEO turnover on strategic change will be enhanced. TMT external social network, ownership nature and industry type all negatively moderate the relationship between CEO turnover and strategic change. TMT external social network and ownership nature have a joint moderating effect between CEO turnover and strategic change. When TMT external social network is small, CEO turnover has a positive effect on strategic change in both state-owned enterprises and non-state-owned enterprises, but the promotion effect is stronger in non-state-owned enterprises. When TMT external social network is large, the positive effect of CEO turnover on strategic change in state-owned enterprises is from strong to weak, but in the non-state-owned enterprises is from weak to strong. TMT external social network and industry type have a joint moderating effect between CEO turnover and strategic change. When TMT external social network is small, CEO turnover has a positive impact on strategic change in high-tech enterprises and non-high-tech enterprises, but the promotion effect is stronger in non-high-tech enterprises. When TMT external social network is large, the positive impact of CEO turnover on strategic change in high-tech enterprises is from strong to weak, but in the non-high-tech enterprises is from weak to strong.

On the basis of previous studies, this paper further expands the research scope of the mechanism of CEO turnover on strategic change, echoing the research arguments of relevant scholars. At the same time, the research results reveal the mechanism of organizational slack, TMT external social network, ownership nature and industry type in the relationship between CEO turnover and strategic change, and further deepen the application of upper echelons theory, resources allocation theory and structuration theory in China. In addition, the research conclusions of this paper also provide reference value for Chinese enterprises in carrying out strategic change, promoting enterprise transformation and improving the level of corporate governance, and help to enhance the understanding and attention of Chinese enterprises to CEO turnover, organizational slack, TMT external social network, strategic change and corporate governance under the background of high-quality economic development.

This paper aims to study a neural network-based fault-tolerant controller to improve the tracking control performance of an unmanned autonomous helicopter with system uncertainty, external disturbances and sensor faults, using the prescribed performance method.

To ensure that the tracking error satisfies the prescribed performance, the authors adopt an error transformation function method. A control scheme based on the neural network and high-order disturbance observer is designed to guarantee the boundedness of the closed-loop system. A simulation is performed to prove the validity of the control scheme.

The developed adaptive fault-tolerant control method makes the system with sensor fault realize tracking control. The error transformation function method can effectively handle the prescribed performance requirements. Sensor fault can be regarded as a type of system uncertainty. The uncertainty can be approximated accurately using neural networks. A high-order disturbance observer can effectively suppress compound disturbances.

The tracking performance requirements of unmanned autonomous helicopter system are considered in the design of sensor fault-tolerant control. The inequality constraint that the output tracking error must satisfy is transformed into an unconstrained problem by introducing an error transformation function. The fault state of the velocity sensor is considered as the system uncertainty, and a neural network is used to approach the total uncertainty. Neural network estimation errors and external disturbances are treated as compound disturbances, and a high-order disturbance observer is constructed to compensate for them.

The financial sector’s growing interest in leveraging artificial intelligence (AI) for forecasting has been noted in recent years. In this chapter, we delve into the application of AI in financial forecasting within Indonesia’s stock market. Our primary focus is to assess how AI’s prediction potential can impact investors and financial regulators in this context. Our review spans existing literature on AI and financial forecasting, recent developments in the Indonesian stock market, and ethical and regulatory concerns that surround AI in finance. Our analysis indicates that AI can enhance forecast accuracy in Indonesia’s stock exchange; however, we must also consider limitations and challenges.

Prosocial lending in online crowdfunding has flourished in recent years, and it has become a new way to fundraise for philanthropy. However, there is almost a 70% user attrition rate in crowdfunding. The purpose of this study is to understand what the lender’s lending experience and social connection influence lender retention of online prosocial lending from a self-determination perspective.

Drawing on self-determination theory (SDT), this research utilizes a quantifiable method for factors of the lender's lending experience and social connection. Additionally, the research constructs economic models to explore the impacts of these factors acting as the necessary conditions for basic psychological needs on lender retention, using a large-scale sample of over 380,000 lenders from Kiva.

The results indicate that, from the lender's lending experience aspect, the loan narratives with more profit language in the last lending and the failure of past participation are negatively related to lender retention. Regarding the lender's social connection aspect, their friends or small lending teams are positively related to lender retention, while whether they are invited and lending team size show negative influence. Furthermore, results indicate the moderating effects of the disclosure of lending motivation.

This research explores the mechanism of lender retention of online prosocial lending, providing a self-determination perspective about how previous experience influences long-term lending behavior. The study offers significant implications for the literature on online philanthropy, SDT and user retention of online platforms. At the same time, the study provides an understanding of the effects of different aspects of SDT.

By discussing the spatial spillover effect and regional heterogeneity of digital economy and green agricultural development level, this paper aims to provide countermeasures and suggestions for the better development of green agriculture in the contemporary era when digital economy is universally developed and at the same time provide development suggestions suitable for green agriculture's development characteristics and initial conditions for different regions.

This paper discusses the theoretical foundation of the digital economy and green agriculture development and utilizes panel data from 30 provinces in China from 2011 to 2018. By employing the Super-Efficiency Slack-based Measure and Malmquist-Luenberger (SBM-ML) model based on unexpected output to measure the total factor productivity of green agriculture and employing the spatial panel Durbin model to empirically test the spatiotemporal effects of the digital economy on green agriculture development from both temporal and spatial dimensions. Finally, the model is tested for robustness as well as heterogeneity.

The research findings are as follows: First, from the perspective of time effect, digital economy has a continuous driving effect on the development of green agriculture and with the passage of time, this effect becomes more and more prominent; second, from the perspective of spatial effect, digital economy has a significant positive impact on the development of local green agriculture, while digital economy has a significant negative impact on the development of surrounding green agriculture. Finally, the impact of digital economy on the development of green agriculture shows significant differences in different dimensions and regions.

As an important driver of economic growth, the digital economy has injected new impetus into agricultural and rural development. Along with the intensifying environmental pollution problems, how to influence the green development of agriculture through the digital economy is a proposition worthy of attention nowadays. This paper analyzes the relationship between the digital economy and agricultural green development in multiple dimensions by exploring the temporal and spatial spillover effects of the digital economy on agricultural green development, as well as the heterogeneity in different dimensions and in different regions and derives policy insights accordingly in order to improve relevant policies.