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Using China’s key audit matters (KAMs) data, this study aims to examine whether negative press coverage alleviates boilerplate KAMs.

This study uses Levenshtein edit distance (LVD) to calculate the horizontal boilerplate of KAMs and investigates how boilerplate changes under different levels of the perceived legal risk.

The findings indicate that auditors of firms exposed to substantial negative press coverage will reduce the boilerplate of KAMs. This association is more significant for auditing firms with lower market share and client firms with higher financial distress. Additionally, the authors find that negative press coverage is more likely to alleviate the boilerplate disclosure of KAMs related to managers’ subjective estimation and material transactions and events. Furthermore, the association between negative press coverage and boilerplate KAMs varies with the source of negative news.

The findings suggest that upon exposure to negative press coverage, reducing the boilerplate of KAMs has a disclaimer effect for auditors.

This paper aims to reveal the interdisciplinarity of information science (IS) from the perspective of the evolution of theory application.

Select eight representative IS journals as data sources, extract the theories mentioned in the full texts of the research papers and then measure annual interdisciplinarity of IS by conducting theory co-occurrence network analysis, diversity measure and evolution analysis.

As a young and vibrant discipline, IS has been continuously absorbing and internalizing external theoretical knowledge and thus formed a high degree of interdisciplinarity. With the continuous application of some kernel theories, the interdisciplinarity of IS appears to be decreasing and gradually converging into a few neighboring disciplines. Influenced by big data and artificial intelligence, the research paradigm of IS is shifting from a theory centered one to a technology centered one.

This study helps to understand the evolution of the interdisciplinarity of IS in the past 21 years. The main limitation is that the data were collected from eight journals indexed by the Social Sciences Citation Index and a small amount of theories might have been omitted.

This study identifies the kernel theories in IS research, measures the interdisciplinarity of IS based on the evolution of the co-occurrence network of theory source disciplines and reveals the paradigm shift being happening in IS.

As convenience and anonymity, people with mental illness are increasingly willing to communicate and share information through social media platforms to receive emotional and spiritual support. The purpose of this paper is to identify the degree of depression based on people's behavioral patterns and discussion content on the Internet.

Based on the previous studies on depression, the severity of depression is divided into four categories: no significant depressive symptoms, mild MDD, moderate MDD and severe MDD, and defined each of them. Next, in order to automatically identify the severity, the authors proposed social media digital cues to identify the severity of depression, which include textual lexical features, depressive language features and social behavioral features. Finally, the authors evaluate a system that is developed based on social media digital cues in the experiment using social media data.

The social media digital cues including textual lexical features, depressive language features and social behavioral features (F1, F2 and F3) is the relatively best one to classify four different levels of depression.

This paper innovatively proposes a social media data-based framework (SMDF) to identify and predict different degrees of depression through social media digital cues and evaluates the accuracy of the detection through social media data, providing useful attempts for the identification and intervention of depression.

This paper investigates the puzzle of mergers and acquisitions’ (M&A) long-term performance through the strategic management perspective. The authors measure the M&A capability construct and test its relationship with the long-term performance of the firms.

The study employs a natural language processing (NLP) methodology to quantify unstructured data from 564 annual reports and 2,602 M&A synopses from January 01, 2013 to December 31, 2016. The authors combine qualitative document analysis with a quantitative method using a multiple regression analysis model.

Among serial acquirers, M&A capability positively relates to long-term firm performance measured by both return on equity and price-to-book value. The authors also find that the size of the company and the number of acquisitions influence the M&A capability, confirming previous results in the literature.

Detailed M&A management plans are usually confidential and not fully reported. Future studies could employ enhanced artificial intelligence tools to measure the M&A capability construct beyond filing reports, encompassing interviews, social media posts, press releases and other unstructured data sources.

Firms can improve their M&A capability by understanding the underlying foundation of the construct provided in the research. Additionally, researchers can build on the methodology employed using advanced NLP tools to measure M&A capability.

Improving their M&A capability would allow firms to better choose their targets and conduct a superior integration process, which could prevent distressing mergers, unnecessary negative social impacts and culture disruption. As a result, the ensuing organization would be stronger, and the long-term performance would improve.

This study addresses gaps in the literature on M&A performance and provides a new empirical method to measure the M&A capability.

This study aims to analyze lean wastes for the poultry sector in Turkey and link lean tools to this study, focusing on identifying each lean waste that affects poultry production and proposing solutions for preventing these lean wastes in the sector. The proposed solutions aim to improve processes by suggesting different lean tools and their applications for the poultry sector.

The study consists of two different applications. First, the waste relationship matrix (WRM) was created to reveal the relationship between seven lean wastes and their importance order. Then, after determining lean tools for eliminating lean wastes, the optimum weight ranking and consistency ratio of the most suitable lean tools were calculated for these wastes and ranked with the best-worst method (BWM).

Results showed that overproduction is the most critical waste that impacts other wastes, followed by defect waste. Due to the nature of the sector, these wastes not only result in economic loss for the company but also in food waste and loss and issues related to animal welfare. Furthermore, the Kaizen approach and 5S implementation are the methods to eliminate these wastes. Detailed discussion on the link between lean tools and lean wastes is provided for the poultry sector.

This is the first study that theoretically and empirically identifies the potential lean waste affecting the poultry sector and provides lean tools for eliminating these wastes. Sector-specific explanations and discussions are presented in the study to show the applicability of lean approaches in the poultry sector to eliminate waste. In addition, this study is the first to integrate the WRM and BWM.

Microribbon with meander type based on giant magnetoimpedance (GMI) effect has become a research hot spot due to their higher sensitivity and spatial resolution. The purpose of this paper is to further optimize the line spacing to improve the performance of meanders for sensor application.

The model of GMI effect of microribbon with meander type is established. The effect of line spacing (Ls) on GMI behavior in meanders is analyzed systematically.

Comparison of theory and experiment indicates that decreasing the line spacing increases the negative mutual inductance and a consequent increase in the GMI effect. The maximum value of the GMI ratio increases from 69% to 91.8% (simulation results) and 16.9% to 51.4% (experimental results) when the line spacing is reduced from 400 to 50 µm. The contribution of line spacing versus line width to the GMI ratio of microribbon with meander type was contrasted. This behavior of the GMI ratio is dominated by the overall negative contribution of the mutual inductance.

This paper explores the effect of line spacing on the GMI ratio of meander type by comparing the simulation results with the experimental results. The superior line spacing is found in the identical sensing area. The findings will contribute to the design of high-performance micropatterned ribbon with meander-type GMI sensors and the establishment of a ribbon-based magnetic-sensitive biosensing system.

The paper aims to identify, prioritize and rank lean practices in the context of an Indian automotive component manufacturing organization using interpretive ranking process (IRP) and interpretive structural modeling (ISM) approaches.

Lean practices are identified from the literature. Then, two hierarchical models were are developed using two distinct modeling approaches – ISM and IRP with expert opinions from an Indian automotive component manufacturing organization to analyze the contextual relationships among the various lean practices and to prioritize and rank them with respect to performance dimensions.

In the study, the hierarchical structural models are developed using ISM and IRP approaches for an Indian automotive component manufacturing organization. In ISM-based modeling, lean practices can be categorized into five levels. Top priority should be given to the motivators followed by value chain, system/technology and organization centric practices. IRP model shows the dominance relationship among the various lean practices with respect to performance dimensions.

The models are constructed from the organizational standpoint to evaluate their impact to the implementation of lean manufacturing. The study leverages the organizations to prioritize limited resources as per the hierarchy. Managers get the inter-linkages and ranking of various lean practices, which leads to a better perspective for the effective implementation of lean. The structural models also assist management to assign proper roles to employees/departments for effective lean implementation.

There is hardly any structural model of lean practices in the literature for clustering, prioritizing and ranking of lean practices. The study fills this gap and develops the hierarchical models of lean practices through IRP and ISM approaches for an Indian automotive component manufacturing organization. The results from both approaches are compared for illustrating the benefits of one over the other.

The paper tests if and to what extent lean management system adoption generates abnormal profitability, and how it accrues over time. Configurational approaches to lean management systems and “S-curve” effects in lean implementation are used to ground the paper's hypotheses and interpret its findings.

Using the emerging view of lean as enterprise-wide management systems, this quasi-experimental study uses a difference-in-differences approach to estimate the abnormal profitability (ROIC) attributable to lean management system adoption. The paper leverages a unique data set of lean adopters nested in a panel data set (19 years) of 2,088 industrial firms matched by industry and firm size. It applies a variety of regression methods (two-way fixed effect panel estimator, propensity score matching, instrumental variable two-stage-least squares) to estimate the size of the abnormal profitability attributable to lean management systems, addressing endogeneity issues related to non-random sampling, omitted variable bias and reverse causation. It also analyzes the cross-firm variability of such abnormal profitability and how it accrues over time.

For the average non-adopter in the sample (44.3 million euro revenues), lean adoption generates abnormal ROIC ranging from 1.4% to 3.9%. These results come into effect approximately three years after starting lean adoption and peak after eight years. While the average abnormal profitability attributable to lean adoption is sizable, it varies significantly across firms and over time. This significant variation is compatible with firms' diverse ability to understand the complex inner workings of lean systems, and to design and implement them so that they improve profitability.

The conceptualization of lean as enterprise-wide management system can be further refined to more effectively categorize the components of lean systems and investigate the nature of their relationships. Lean system adoption measurement can be fine-tuned to better capture cross-firm and longitudinal heterogeneity. Future work can explore other dependent variables of interest to different stakeholders including shareholders' value, employment and environmental and social sustainability.

The financial benefits of adopting lean can be reaped to the extent to which managers embrace lean as a philosophy and implement it pervasively in the organization. A firm can use the study's estimates as a basis for making calculations about the returns of investment in lean adoption. The paper also shows that “getting the lean system right” makes a significant difference in terms of abnormal profitability, which is twice as large for the best lean adopters..

Compared with the promises of many lean proponents and supporters, the paper provides a more realistic view of what to expect from lean adoption in terms of profitability. Adopting lean as a comprehensive, enterprise-wide management system is not a universal panacea, but a complex endeavor, characterized by multiple complex decisions that require considerable capabilities, coordinated efforts and consistency of action.

Differently from extant research, this study does not study the correlation between the adoption of lean operation practices and financial performance but focuses on the abnormal profitability generated by the adoption of lean as a pervasive, enterprise-wide management system. Its research design allows to identify the differential profitability attributable to lean adoption and documents that it accrues non-linearly.