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Self-presentation has emerged as a pivotal marketing strategy for service providers seeking to craft virtual images in the peer-to-peer (P2P) accommodation sector. However, the literature lacks an understanding of conversational self-presentation, which offers more informal and personal communication.

Drawing upon social interaction theory and uncertainty reduction theory, this study explores the impact of conversational self-presentation and its interplay with space sharing and review ratings on customer purchases.

Utilizing the fixed effects model on a panel dataset comprising 498,817 observations from Airbnb, we discover a positive association between conversational self-presentation and customer purchases. Furthermore, our analysis reveals that space sharing reinforces this positive effect, while review ratings tend to diminish it. A deeper mechanism analysis indicates that perceived authenticity plays a mediating role in the relationship between conversational self-presentation and customer purchases.

This study highlights the importance of conversational communication in enhancing host–guest relationships under information asymmetry. However, the proposed model can be extended to other accommodation-sharing platforms in various regions, identifying whether cultural differences exist in explaining the importance of conversational self-presentation.

Marketers are suggested to build a harmonious customer–brand relationship and achieve superior performance through effective online communication.

This study adds valuable insights to the literature about self-presentation, social interaction and customer behavior by revealing the significance of conversational self-presentation in driving the growth of P2P accommodation businesses.

The current research delves into how different cues in messages (such as argument quality, usefulness and informativeness) and cues related to the source (such as credibility and expertise) contribute to the perceived credibility of electronic word-of-mouth (eWOM). The investigation also explores whether source cues influence the overall impact of message cues.

This study synthesizes findings from 100 previous empirical works through the application of meta-analysis.

The outcomes affirm the presence of both systematic and heuristic processing, the additive effects of both message and source cues and the bias effects of source cues. Moreover, the study identifies a connection between eWOM credibility and behavioral intention. Expanding on this, the research discovers that users’ tendency to avoid uncertainty moderates the impact of message and source cues on their judgment of eWoM credibility.

The research contributes to the eWOM literature by providing a heuristic-systematic model of eWoM credibility judgments. It provides new insights for online sellers, who can benefit from eWoM by fostering potential buyers' behavioral intention to purchase.

The study is aimed at examining the impact of ESG on the financial performance (FP) of firms and determining the difference between the impact of ESG on market-oriented financial performance measure (Tobin’s Q) and internal productivity-based financial measure (ROA). The study has also explored the influence of managerial ability and institutional quality as moderating variables on the relation between ESG and the financial performance of firms (both measures of FP: Tobin’s Q and ROA).

The study is quantitative exploratory and uses panel data of 687 publicly listed companies from the year 2013–2023. Data has been acquired from the reputed data providers and OLS regression has been used for panel data analysis with fixed effects.

The study reaffirms the positive impact of ESG on the financial performance of firms. Each pillar of ESG (environmental, social, and governance) has been found positively related to both measures of financial performance (Tobin’s Q and ROA). The study reveals that managerial ability and institutional quality, acting as supplementary variables, moderate the relationship between ESG and financial performance of firms.

A limited sample comprising data from only 687 firms was used for the analysis. The latest data was not available, therefore, data from 2013 to 2023 was used in the study.

This study indicates that ESG practices, which are mostly discretionary in Emerging Economies, can be induced through institutional pressures and ensuring higher quality managers. Policymakers in government institutions have to determine the inefficiencies, corrupt practices, and inconsistencies in policies that lower the effectiveness of institutions making them business-unfriendly. At the organizational level, policymakers need to ensure that responsible positions in the organization are held by managers with higher managerial ability. It is also to be ensured by shareholders that managers do not over-invest in ESG-related projects, particularly in organizations with weaker financial status. For managers, it is important to understand the positive benefits associated with ESG, even though they are in the long term.

In Emerging Economies, the official monitoring and regulatory mechanisms are weak, and lack a supportive attitude toward ESG initiatives. Voluntary and proactive firm-level environmental and social initiatives need to be encouraged and rewarded by institutions with public acknowledgment. ESG should be given priority by organizations for improving the quality of services and better social impact of businesses on society.

Most of the past research explored the impact of ESG on financial performance in advanced countries or in emerging markets in a single/limited number of countries or industries. Also, past studies investigated the impact of institutional quality and managerial ability on ESG/financial performance in separate models. Conversely, this study has used a multi-country and multi-industry sample for more generalizable findings. Against the backdrop of the institutional environment of Emerging Economies, the study extends Institutional Theory and Upper Echelon Theory to include the role of managerial ability and institutional quality in the relationship between ESG and firms’ financial performance.

The purpose of this study is to systematically analyze the wear of cylindrical needle bearings in rotary vector reducers under temperature rise and identify the influencing factors.

Based on the dynamic characteristics of the RV-20E reducer, the time-varying contact force of the cylindrical needle bearing and the entrainment speed of the inner and outer raceways were calculated. A mixed elastohydrodynamic lubrication model of the needle bearing, considering friction and temperature rise, was established using a dynamic rough tooth surface model. The model solved for the oil film thickness, contact stress and wear conditions of the bearing raceway contact area. The effects of the number of rolling needles, the diameter of rolling needles and surface strength on the wear characteristics were analyzed.

The results of this study show that the oil film thickness, oil film pressure and surface scratches of cylindrical needle bearings exhibit an uneven, patchy distribution under the combined effects of friction and temperature rise. When the radius of the rolling needle is less than 1.44 mm, inner ring wear is less than outer ring wear. Conversely, when the radius exceeds 1.44 mm, inner ring wear is greater. The optimal rolling needle radius is 1.6 mm. Increasing the number of rolling needles and enhancing the yield strength of the contact surface significantly extend bearing life.

This study provides valuable recommendations for optimizing bearing structural parameters and material characteristics in the design of rotary vector reducers.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2024-0242/

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.

A wealth of studies have identified numerous antecedents to online self-disclosure. However, the number of competing theoretical perspectives and inconsistent findings have hampered efforts to obtain a clear understanding of what truly influences online self-disclosure. To address this gap, this study draws on the antecedent-privacy concern-outcome (APCO) framework in a one-stage meta-analytical structural equation modeling (one-stage MASEM) study to test a nomological online self-disclosure model that assesses the factors affecting online self-disclosure.

Using the one-stage MASEM technique, this study conducts a meta-analysis of online self-disclosure literature that comprises 130 independent samples extracted from 110 articles reported by 53,024 individuals.

The results reveal that trust, privacy concern, privacy risk and privacy benefit are the important antecedents of online self-disclosure. Privacy concern can be influenced by general privacy concern, privacy experience and privacy control. Furthermore, moderator analysis indicates that technology type has moderating effects on the links between online self-disclosure and some of its drivers.

First, with the guidance of the APCO framework, this study provides a comprehensive framework that connects the most relevant antecedents underlying online self-disclosure using one-stage MASEM. Second, this study identifies the contextual factors that influence the effectiveness of the antecedents of online self-disclosure.

Estimation of solar cell parameters, mathematical modeling and the actual performance analysis of photovoltaic (PV) cells at various ecological conditions are very important in the design and analysis of maximum power point trackers and power converters. This study aims to propose the analysis and modeling of a simplified three-diode model based on the manufacturer’s performance data.

A novel technique is presented to evaluate the PV cell constraints and simplify the existing equation using analytical and iterative methods. To examine the current equation, this study focuses on three crucial operational points: open circuit, short circuit and maximum operating points. The number of parameters needed to estimate these built-in models is decreased from nine to five by an effective iteration method, considerably reducing computational requirements.

The proposed model, in contrast to the previous complex nine-parameter three-diode model, simplifies the modeling and analysis process by requiring only five parameters. To ensure the reliability and accuracy of this proposed model, its results were carefully compared with datasheet values under standard test conditions (STC). This model was implemented using MATLAB/Simulink and validated using a polycrystalline solar cell under STC conditions.

The proposed three-diode model clearly outperforms the earlier existing two-diode model in terms of accuracy and performance, especially in lower irradiance settings, according to the results and comparison analysis.

The purpose of current study aims to provide a different perspective on customer-based brand equity (CBBE) and integrate this with previous brand equity theory to contribute to the brand equity literature.

Proposed hypotheses were verified using structural equation modelling (SEM) with multiple datasets. Study 1 collected data from 574 foreign tourists and 624 domestic tourists of culinary tourism. Study 2 used 1,020 customers from anti-epidemic restaurants, and Study 3 investigated 464 hotel customers’ perceptions of customer-based brand equity.

Building on the mediation-moderation model, the present study posits that perceived quality relates to brand loyalty through brand image and brand awareness of using 2,682 participants. Specifically, we argue that this indirect relationship exhibits a difference moderated pattern in which motivation and hedonic function are most likely to benefit from revisit destinations for tourists when they are moderate. We further explored the new anti-epidemic concepts of COVID-19 and identified restaurant operation as an important moderator that influences customer image of restaurant revisit.

Until now, no tourism and hospitality studies have addressed these unsolved problems in an integrated manner. This study was to investigate the brand equity development process.

Safety management plays an important part in coal mine construction. Due to complex data, the implementation of the construction safety knowledge scattered in standards poses a challenge. This paper aims to develop a knowledge extraction model to automatically and efficiently extract domain knowledge from unstructured texts.

Bidirectional encoder representations from transformers (BERT)-bidirectional long short-term memory (BiLSTM)-conditional random field (CRF) method based on a pre-training language model was applied to carry out knowledge entity recognition in the field of coal mine construction safety in this paper. Firstly, 80 safety standards for coal mine construction were collected, sorted out and marked as a descriptive corpus. Then, the BERT pre-training language model was used to obtain dynamic word vectors. Finally, the BiLSTM-CRF model concluded the entity’s optimal tag sequence.

Accordingly, 11,933 entities and 2,051 relationships in the standard specifications texts of this paper were identified and a language model suitable for coal mine construction safety management was proposed. The experiments showed that F1 values were all above 60% in nine types of entities such as security management. F1 value of this model was more than 60% for entity extraction. The model identified and extracted entities more accurately than conventional methods.

This work completed the domain knowledge query and built a Q&A platform via entities and relationships identified by the standard specifications suitable for coal mines. This paper proposed a systematic framework for texts in coal mine construction safety to improve efficiency and accuracy of domain-specific entity extraction. In addition, the pretraining language model was also introduced into the coal mine construction safety to realize dynamic entity recognition, which provides technical support and theoretical reference for the optimization of safety management platforms.

Given the progressive rise of online health communities (OHC) that have predominantly changed health delivery services, healthcare organizations still face tremendous challenges of low patient participation and lack of high-quality contribution to OHC. Prior scholars indicated that inducing patient value co-creation behavior (VCB) is substantially beneficial for the sustainable growth of OHCs. However, what drives patients' behavior to co-create value is still unknown. To fill this important gap, this study used the service-dominant logic of value co-creation theory and face (mianzi in Chinese) literature to discover how patient co-creation attitude (CA) affects patient VCB. Also, this study aimed to explore the joint mechanism of how face gain (FG) and face loss (FL) impact patients' VCB in OHCs.

The survey data of 322 patients actively using OHC in China were analyzed via partial least squares structural equation model (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA).

The results revealed that patient CA positively influences VCB, that is participation behavior (PB) and citizenship behavior (CB). Face gain (FG) strengthens the impact of CA and patient PB and CB, whereas face loss (FL) weakens the impact of CA and patient PB and CB. Furthermore, the fsQCA findings signify the robustness of the study model.

This study explores the multifaceted mechanism of patient value co-creation in OHC and discloses the crucial role of face for the first time. Further, the novel findings of this study provide a robust framework for advancing the understanding of important drivers of patient VCBs that significantly helps healthcare service providers and OHC managers to sustain OHCs.