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Advances in Econometrics is a series of research volumes first published in 1982 by JAI Press. The authors present an update to the history of the Advances in Econometrics series. The initial history, published in 2012 for the 30th Anniversary Volume, describes key events in the history of the series and provides information about key authors and contributors to Advances in Econometrics. The authors update the original history and discuss significant changes that have occurred since 2012. These changes include the addition of five new Senior Co-Editors, seven new AIE Fellows, an expansion of the AIE conferences throughout the United States and abroad, and the increase in the number of citations for the series from 7,473 in 2012 to over 25,000 by 2022.

This study aims to investigate the impact of supply chain concentration (SCC) on corporate research and development (R&D) investment and determine the moderating roles of industry concentration and financing constraints on the relationship between SCC and R&D investment.

The study collected data from Chinese listed companies, used the fixed effects model to test the research hypotheses and further used the two-stage Heckman test and propensity score matching (PSM) to address potential endogeneity issues.

The result reveals a negative impact of SCC on corporate R&D investment. In addition, industry concentration mitigates the negative impact of SCC on corporate R&D investment, but financing constraints strengthen the negative impact.

This study introduces the concept of SCC and empirically tests its effect on R&D investment, further explaining the lack of corporate innovation. This study inspires companies to strengthen SC management and weigh the level of SCC with environmental factors.

The purpose of our study is to investigate how a manufacturing plant’s internal operations along with its network of connections (upstream and downstream) can have an impact on its recovery time from a disruption. The authors also examine the inverse-U impact of complexity. Finally, the authors test the moderating role that business continuity management plans (BCP) at the plant level have on recovery time.

To test our hypotheses, the authors partnered with Resilinc Corporation, a Silicon Valley-based provider of supply chain risk management solutions to identify focal firms’ suppliers, customers and plant-level data including information on parts, manufacturing activities, bill of materials, alternate sites and formal business continuity plans. The authors employed censored data regression technique (Tobit).

Several important findings reveal that the plant’s internal operations and network connections impact recovery time. Specifically, the number of parts manufactured at the plant as well as the number of internal plant processes significantly increase disruption recovery time. In addition, the number of supply chains (upstream and downstream) involving the plant as well as the echelon distance of the plant from its original equipment manufacturer significantly increase recovery time. The authors also find that there exists an inverted-U relationship between complexity and recovery time. Finally, the authors find partial support that BCP will have a negative moderating effect between complexity and recovery time.

This research highlights gaps in the literature related to supply chain disruption and recovery. There is a need for more accurate methods to measure recovery time, more research on recovery at the supply chain site level and further analysis of the impact of supply chain complexity on recovery time.

There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This chapter extends the Gandhi, Navarro, and Rivers (2020) proxy variable framework for structurally identifying production functions to a more general case when latent firm productivity is multi-dimensional, with both factor-neutral and (biased) factor-augmenting components. Unlike alternative methodologies, the proposed model can be identified under weaker data requirements, notably, without relying on the typically unavailable cross-sectional variation in input prices for instrumentation. When markets are perfectly competitive, point identification is achieved by leveraging the information contained in static optimality conditions, effectively adopting a system-of-equations approach. It is also shown how one can partially identify the non-neutral production technology in the traditional proxy variable framework when firms have market power.

This study aims to investigate specific green-brand affect in terms of commitment and connection through the morality–mortality determinants of consumer social responsibility and the assumptions of terror management theory in the proposed three-layered framework. Religiosity serves as a moderator within the framework.

Data are collected in Taipei, Taiwan, while quota sampling is applied, and 420 valid questionnaires are collected. The partial least squares technique is applied for data analysis.

With the contingent role of religiosity, consumer social responsibility influences socially conscious consumption, which in turn drives the commitment and connection of green-brand affect. The death anxiety and self-esteem outlined in terror management theory influence materialism, which then drives green-brand commitment; however, contrary to expectations, they do not drive green-brand connection.

By considering green brands beyond their cognitive aspects and into their affective counterparts, morality–mortality drivers of green-brand commitment and green-grand connection are explored to provide unique contributions so as to better understand socially responsible consumption.

This study aims to investigate the presence of the audit partner ethnicity on audit fees within the Indonesian context.

The sample consists of 803 firm-year observations from the Indonesia Stock Exchange during the period of 2014–2018. The study uses fixed-effect regression analysis to examine the relationship between audit partner ethnicity and audit fees.

This study reveals that firms audited by audit partners from the main ethnic group demonstrate lower audit fees, indicating a more extensive audit business network for this particular group of auditors compared to those from minority ethnic groups. Particularly, the study finds that firms audited by audit partners from the three largest ethnicities, namely, Balinese, Javanese and West Sumatranese, are associated with lower audit fees compared to others. These findings further contribute to the existing narrative and literature that highlight the ethnic background of audit partners as a form of social capital that influences lower audit fees.

This study provides valuable practical and academic implications regarding the impact of audit partner ethnicity on audit fees. The findings highlight the importance for audit firms to strive for a balanced representation of ethnic diversity in their auditor characteristics, as it can positively influence both governance and marketing strategies. By recognizing and addressing the significance of ethnic diversity among audit partners, firms can enhance their overall effectiveness and success in the auditing profession.

This study makes a unique contribution by providing empirical data on audit pricing theory in Indonesia, specifically focusing on the role of ethnic diversity as a determinant of audit pricing. Previous research has not extensively explored the connection between auditor ethnicity and audit fees, particularly in relation to the business network as a channel mechanism. The theoretical explanations for the fee differentials have also been limited in prior studies. The current study addresses this gap by offering a theoretical basis that highlights the advantage of the dominant ethnic group in establishing an efficient audit market system. Consequently, these auditors are able to charge lower fees to clients without compromising on the quality of their services. This finding aligns with the existing literature on audit fees and underscores the importance of the main ethnic group in fostering an effective audit market, resulting in lower audit fees compared to mixed audit markets.

That knowledge acquisition from external sources can play a pivotal role in product design is a well-known fact. However, knowledge acquisition need not play a pivotal role in every context; it is also documented to have a dark side (i.e. negative impacts). Specifically, given that product stewardship, by definition, calls on each party in the product life cycle – including suppliers – to share responsibility for the environmental impact of products, the purpose of this study is to answer the question “whether knowledge acquired from suppliers plays a beneficial role in the context of product stewardship?”

This study focuses on the effect of knowledge acquisition on product stewardship and its subsequent effect on environmental performance. Given that the effect of knowledge acquisition could be moderated by firm-specific and relational factors, this study also considers the moderating role of knowledge exploitation and supplier opportunism. Using primary data, the hypotheses are tested using two-stage hierarchical ordinary least squares regression models involving valid instruments.

Though extant research doubts that knowledge acquisition will always be beneficial, this study adheres to the tenets of knowledge-based view and hypothesize that knowledge acquisition is pivotal to product stewardship and its subsequent impact on environmental performance. But the results suggest an intriguing double-edged effect of knowledge acquisition; while its direct effect on product stewardship is nonsignificant, it seemed to have a significant positive moderating effect on the relationship between product stewardship and environmental performance. But whenever knowledge exploitation and supplier opportunism are maintained at ideal levels, this double-edged effect of knowledge acquisition is successfully negated.

While knowledge acquisition is key for new product design, its specific role in the product design that incorporates environmental considerations is still not clear. By proposing that knowledge acquisition could instead have a double-edged effect within the unique context of product stewardship, the study makes an invaluable contribution to the extant literature on knowledge management within supply chain relationships.

The purpose of this study is to address the generalised lack of guidance on ethical treatment of corporate (e.g. non-research) data in higher education institutions, by focusing on the case of the University of Queensland (Brisbane, Australia). No actionable framework is currently available in the country to govern the ethical usage of corporate data. As such, this research takes a stakeholder-centred approach to data ethics; the lived experience of the stakeholders involved coupled with a theory-based ethical framework allowed the authors build to build a framework to guide ethical data practice.

Adopting a revised canonical action research approach focused on intervention on the context, the authors conducted a review of the literature on ethical usage of data in higher education institutions; administered one survey to university students (n = 168); and facilitated three workshops with professional staff (two) and students (one).

Collected data highlighted how, among other themes, the role and ethical importance of transparency was the dominant claim among all stakeholder groups. Findings helped the authors develop an Enhanced Enterprise Data Ethics Framework (EEDEF) emphasising transparency and stakeholder-centricity.

Legislation is the driver to regulate the use of corporate data in higher education; however, this can be problematic because legislation is retrospective, lacks normativity and offers scarce directions for cases that do not exactly follow within the legislative mandate. In light of these regulatory limitations, the authors’ EEDEF offers operators guidance on how to ethically manage corporate data in the higher education environment.

This study fills gaps in praxis and theory; that is the lack of literature and guiding ethical frameworks to inform data practice in higher education. This research fosters a more ethical data management by virtue of genuine and authentic engagement with stakeholders and emphasises the importance of strategic decision-making and maturity of data culture in the higher education sector.

The results of this study have significant policy implications for charting a new course toward enhancing agricultural productivity among Chinese farmers.

By establishing a rural household decision-making model based on the transfer market of farmland operation rights, this paper systematically analyzes the effects of land transfer-in and land transfer-out on the productivity (per labor income) of rural households. The authors conducted basic regression analysis and robustness tests using propensity score-matching and proxy variable approaches based on the micro survey data from rural households in 30 counties in 21 provinces/municipalities/autonomous regions in 2013.

After the completion of land transfer, the total productivity of rural households transferring in lands will increase with an increase in the agricultural productivity; the total productivity of rural households transferring out land will increase due to a rise in non-agricultural productivity and the absolute total productivity of rural households not involved in land transfer will remain unchanged.

Unlike previous literature, this paper discusses the impacts of land transfer-in and transfer-out on total productivity, agricultural productivity and non-agricultural productivity among various rural households (i.e. those transferring in land, transferring out land or which are self-sufficient).