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The purpose of this paper is to unearth various dimensions of employee experience (EX) and explore how pandemic impacted various EX factors using online employee reviews. The authors identify employee-discussed EX-factors and quantify the associated sentiments and importance.

This paper employs Latent Dirichlet Allocation on the online employee reviews to identify the key EX-factors. The authors probe sentiments and importance associated with key EX-factors using sentiment analysis, importance analysis, regression analysis and dominance analysis.

The result of topic modeling identifies 20 EX-factors that shape overall EX. While skill development plays a major role in shaping overall EX, employees perceived Salary and Growth as the most important EX-factor and expressed negative sentiments during the pandemic. Employee sentiments significantly influence overall EX.

When employees have extensive change experience, managers should consider various facets of EX to manage the smooth change and deliver a better EX. This research offers key EX-factors to be considered by managers while dealing with employees. Online employee reviews websites are recommended to include the identified key EX-factors to comprehend the holistic EX.

This study contributes to the growing literature on the employee experience as a concept by identifying various EX-factors. The authors expand the extant EX scales by identifying an inclusive and updated set of EX-factors.

The purpose of this study was to examine the moderating role of institutional ownership on the relationship between board gender diversity and earnings management (EM) among listed firms in East African Community (EAC) partner states.

The study used a sample of 71 firms listed in the EAC partner states over 2011–2020. Data were handpicked from the individual firm's audited annual financial reports. Based on the results of the Hausman test, the study used the results of the fixed-effect regression model to test the hypotheses. To test the robustness of the results, the study employed an alternative measure of EM and two additional econometric techniques, including the pooled ordinary least squares (OLS) and the system generalized method of moments (GMM).

The empirical findings revealed that female directors improve the board's effectiveness in monitoring managerial roles. Specifically, the results showed a significantly negative relationship between the proportion of women in the corporate board and EM (as measured by discretionary accruals (DAs)). The findings further revealed an inverse relationship between the proportion of institutional ownership and EM. Finally, the results further demonstrated that institutional ownership enhances the role of board gender diversity in mitigating EM among listed firms in the EAC.

The findings of this study may be useful to managers, investors and regulators in assessing the role of institutional ownership and women's participation on corporate boards as a strategy for alleviating unethical manipulation of earnings.

The findings of this study contribute to the growing concern on gender inequality, especially the marginalization of women from the paid labor force and decision-making. The findings highlight the importance of having more women in the corporate board since this may help in mitigating corporate fraud. Similarly, the findings highlight the importance of institutional ownership as a corporate governance (CG) tool.

Previous studies have reported mixed empirical results on whether board gender diversity mitigates EM. To the best of the author's knowledge, this is the first paper to fill the existing gap by exploring whether institutional ownership moderates the relationship between board gender diversity and EM among listed firms in the EAC.

The current study aims to analyze the linkage among bank competition, liquidity and loan price in an interconnected bank network system.

The study employs the Lerner index to estimate bank power; Granger non-causality for estimating competition, liquidity and loan price network structure; principal component for developing competition network index, liquidity network index and price network index; and panel VAR and LASSO-VAR for analyzing the dynamics of interactive network effect. Current work considers 33 Indian banks, and the duration of the study is from 2010 to 2020.

Network structures are concentrated during the economic upcycle and dispersed during the economic downcycle. A significant interaction among bank competition, liquidity and loan price networks exists in the Indian banking system.

The study meaningfully contributes to the existing literature by adding new insights concerning the interrelationship between bank competition, loan price and bank liquidity networks. While enhancing competition in the banking system, the regulator should also pay attention toward making liquidity provisions. The interactive network framework provides direction to the regulator to formulate appropriate policies for managing competition and liquidity while ensuring the solvency and stability of the banking system.

The study contributes to the limited literature concerning interactive relationship among bank competition, liquidity and loan price in the Indian banks.

This study aims to explore the role of the linguistic style used in the brand-posted social media content on consumer engagement in the Fintech domain.

A total of 3,286 tweets (registering nearly 1.35 million impressions) published by 10 leading Fintech unicorns in India were extracted using the Twitter API. The Linguistic Inquiry and Word Count (LIWC) dictionary was used to analyse the linguistic characteristics of the shared tweets. Negative Binomial Regression (NBR) was used for testing the hypotheses.

This study finds that using drive words and cognitive language increases consumer engagement with Fintech messages via the central route of information processing. Further, affective words and conversational language drive consumer engagement through the peripheral route of information processing.

The study extends the literature on brand engagement by unveiling the effect of linguistic features used to design social media messages.

The study provides guidance to social media marketers of Fintech brands regarding what content strategies best enhance consumer engagement. The linguistic style to improve online consumer engagement (OCE) is detailed.

The study’s findings contribute to the growing stream of Fintech literature by exploring the role of linguistic style on consumer engagement in social media communication. The study’s findings indicate the relevance of the dual processing mechanism of elaboration likelihood model (ELM) as an explanatory theory for evaluating consumer engagement with messages posted by Fintech brands.

To cater to the senior tourist market, it is essential to comprehend the factors motivating and deterring them from international travel post-COVID-19. This study aims to focus on senior citizens’ destination choice intentions and aims to develop a model that prioritizes positive and negative factors leading to international travel destination choices. It uses push–pull factors, perceived travel risks (PTRs) and perceived travel constraints (PTCs).

Decision-making trial and evaluation laboratory (DEMATEL) and fuzzy technique for order of preference by similarity to ideal solution (Fuzzy TOPSIS) are two multi-criteria decision-making (MCDM) techniques used to identify connections between variables and determine their relative importance in the decision-making model.

DEMATEL found push and pull factors are “effects” while PTCs and PTRs are “causes” affecting senior citizens’ destination choices. Push factors and PTCs have a greater impact than pull factors and PTRs. Fuzzy TOPSIS highlighted “improving health and wellness” and “self-fulfillment and spirituality” as key push factors, “health safety and security quotient” as the most important pull factor, and “interpersonal constraints” as the most critical PTC. Finally, “health risks” is the top PTR.

This paper adds to the tourism literature by looking at the relationship between senior tourists’ motivation, PTRs and PTCs and showing how the subfactors affect their choice of destination rank. The data analysis techniques used in this study are also novel, having never been used before in senior tourism research. Finally, even though there is a lot of research on senior tourism, not much is known about how Indian senior tourists act. In light of this study’s findings, practical recommendations were offered to tourism stakeholders worldwide, interested in tapping into the market of Indian outbound senior tourists or repositioning product or destination offerings to take this promising market or similar markets into account.

为了成功迎合蓬勃发展的老年旅游市场, 了解激励和阻止老年人国际旅行的因素尤为重要, 尤其是在 COVID-19 之后。本研究侧重于老年人的目的地选择意向, 并基于推拉因素、感知旅行风险 (PTR) 和感知旅行限制 (PTC), 旨在开发影响老年人国际旅游目的地选择的积极和消极因素的模型。

决策试验和评估实验室 (DEMATEL), 和与理想解决方案相似度的模糊偏好顺序 (Fuzzy TOPSIS) 是两种多标准决策 (MCDM) 技术, 用于识别变量之间的联系并找出它们在决策模型中的相对重要性。

DEMATEL的结果表明, 推力和拉力因素是“影响”, 而感知旅行约束（PTC）和感知旅行风险（PTR）是影响老年人目的地选择意愿的因素中的“原因”。推动因素和 PTC 比拉动因素和 PTR 发挥更重要的作用。 Fuzzy TOPSIS分析结果表明, “改善健康”和“自我实现和精神”是推动因素下最重要的因素。此外, 目的地的“健康安全商数”是拉动因素中最重要的, “人际约束”是PTC中最重要的。最后, 研究结果表明, “健康风险”是 PTR 中最重要的。

本文通过评估旅游动机、PTR 和老年游客 PTC 之间的相互关系, 为现有的旅游文献做出了贡献。此外, 该研究展示了影响老年游客目的地选择意愿的因素中各个子因素的比较优先级。本研究中使用的数据分析技术也很新颖, 以前从未在老年人旅游研究中使用过。最后, 虽然对老年旅游有丰富的研究, 但印度老年旅游者的行为相对不为人知。研究结果向有兴趣进入印度出境老年游客市场或重新定位产品或目的地的全球旅游利益相关者提供了切实可行的建议, 以考虑这个有前景的市场或类似市场。

Para atender a un mercado turístico de la tercera edad, es esencial comprender los factores que les motivan y les disuaden de realizar viajes internacionales tras el COVID-19. Este estudio se centra en las intenciones de elección de destino de las personas mayores y pretende desarrollar un modelo que priorice los factores positivos y negativos que conducen a la elección de un destino de viaje internacional. Utiliza los factores push-pull, los riesgos de viaje percibidos (PTR) y las limitaciones de viaje percibidas (PTC).

Decision Making Trial and Evaluation Laboratory (DEMATEL) y Fuzzy Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) son dos técnicas de toma de decisiones multicriterio (MCDM) utilizadas para identificar las conexiones entre variables y determinar su importancia relativa en el modelo de toma de decisiones.

DEMATEL descubrió que los factores de empuje y atracción son “efectos,” mientras que las PTC y las PTR son “causas” que afectan a las elecciones de destino de las personas mayores. Los factores de empuje y los PTC tienen un mayor impacto que los factores de atracción y los PTR. El Fuzzy TOPSIS destacó la “mejora de la salud y el bienestar” y la “autorrealización y espiritualidad” como factores de empuje clave, el “cociente de seguridad y protección de la salud” como el factor de atracción más importante y las “limitaciones interpersonales” como el PTC más crítico. Por último, los “riesgos para la salud” son el principal PTR.

Este artículo se suma a la literatura turística al estudiar la relación entre la motivación de los turistas sénior, los PTR y los PTC y mostrar cómo afectan los subfactores a su elección del destino. Las técnicas de análisis de datos empleadas en este estudio también son novedosas, ya que nunca se habían utilizado en la investigación sobre el turismo senior. Por último, aunque existen muchas investigaciones sobre el turismo sénior, el comportamiento de los turistas de la tercera edad en la India es relativamente desconocido. A la luz de los resultados del estudio, se ofrecen recomendaciones prácticas a las partes interesadas en el turismo de todo el mundo, interesadas en aprovechar el mercado de los turistas senior indios emisores o en reposicionar la oferta de productos o destinos para tener en cuenta este prometedor mercado o mercados similares.

Drawing on the stimulus–organism–response framework, this study examined the environmental stimuli driving tourists' internal, or organismic, states. In addition, the authors investigated the association of the identified organismic variables with the response variables during the COVID-19 pandemic. Specifically, the study examined how the associations between tourists' anticipation of recovery and the national government's smart governance, on one hand, and tourists' desire to travel domestically, their attitude toward domestic travel and their willingness to exhibit prosocial behaviors, on the other, further drive the satisfaction they derive from domestic travel.

The authors used an online questionnaire to collect self-report, single-wave data from individuals residing in India, an emerging market (N = 421).

The findings demonstrate (1) the association of anticipated recovery on the desire to travel and prosocial behavior; (2) the association of smart governance on attitude (although negative); (3) the association of desire, attitude and prosocial behavior on satisfaction; and (4) the lack of any moderation effect for perceived severity.

This study is the first empirical study to investigate the impact of tourists' perceptions and dispositions and the efficacy of the national government on tourists' desire to travel domestically and on their satisfaction with domestic travel. The findings can help emerging market multinationals and global brands engage better with domestic consumers in emerging markets within the context of the current pandemic. In addition, the findings can help to prepare these players to handle future disruptions caused by global health contingencies.

This study aims to explore supply chain disruptions during the COVID-19 pandemic in the small and medium enterprise (SME) sector in Oman. This study analyzes the impact on selected supply chain drivers – facilities, inventory, transportation and sourcing. It further intends to explore whether the supply chain challenges faced by the SME sector in Oman impact their overall performance.

This study follows the quantitative technique of structural equation modeling to examine the proposed hypotheses. Data were collected electronically from SME managers/owners/entrepreneurs. All items were adopted and measured using a five-point Likert scale. One hundred and four complete and usable responses were received and considered.

The data was analyzed using SPSS and PLS statistical software. The model has been supported empirically, and the results showed a significant relationship between supply chain drivers and SMEs’ overall performance in Oman, except for supply chain inventory. The results have demonstrated that the COVID-19 pandemic has affected the SMEs’ supply chain drivers in Oman and, consequently, their overall performance.

The results of this research can drive the development and implementation of a supply chain management strategy. This research will help policymakers induce the performance of SMEs affected by the COVID-19 pandemic. It would further enhance strategic sourcing and supplier performance considering the developed practices associated with the resource-based view.

The originality of the current study lies in its ability to empirically test two models within the Omani SMEs context while considering the supply chain drivers as a single variable or dividing it into four separate independent variables. This study would provide a preview for scholars for such empirical investigation and serve as a reference for policymakers and practitioners to maintain a management system of crises that may protect the SME supply chain drivers.

The impact of COVID-19 has caused a recession in economies all over the world. In this context, the current study aims to analyze the prevailing economic scenario using a machine learning approach and suggest sustainable measures to recover the global economy taking the case of Make in India (MII) initiative of developing the economy as a base for the study.

A well-known topic modeling technique – Latent Dirichlet allocation (LDA) algorithm has been employed to extract useful information characterizing the existing state of selected sectors under the MII initiative alongside catalytic policies that have been implemented for the same. The textual data acts as the base of the study upon which suggestions are provided.

The findings obtained suggest that digital transformation will play a key role in concerned sectors to optimize the performance of manufacturing organizations. Additionally, inter-relationship between Key Performance Indicators for the economy's revival is crucial for effective utilization of foreign direct investment resources.

The novel efforts to utilize MII initiative as a case present crucial information which can be used by policy makers and various other stakeholders across the globe to enhance decision-making and draft legislation across different sectors to empower the economy.

The study presents a novel approach to utilize the MII initiative by identifying important measures for crucial sectors and associated policies that have been presented by employing a text mining approach which in itself makes it unique in its contribution to research literature.

The majority of previous studies made on Recycled Concrete Aggregates (RCA) are limited to the utilisation of non-structural grade concrete due to unfavourable physical characteristics of RCA including the higher absorption of water, tending to increased water requirement of concrete. This seriously limits its applicability and as a result it reduces the usage of RCA in structural members. In the present study, the impact of hybrid fibres on cracking behaviour of RCA concrete beams along with the inclusion of reinforcing steel bars under two-point loading system exposed to different sustained elevated temperatures are being investigated.

RCA is substituted for Natural Coarse Aggregates (NCA) at 0, 50 and 100 percentages. The study involves testing of 150 mm cubes and beams of size (700 × 150 × 150) mm, i.e. with steel reinforcing bars along with the addition of 0.35% Steel fibres+ 0.15% polypropylene fibres. The specimens are being exposed to temperatures from 100° to 500°C with 100° interval for 2 h. Studies were made on the post crack analysis, which includes the measurement of crack width, crack length and load at first crack. The crack patterns were analysed in order to understand the effect of fibres and RCA at sustained elevated temperatures.

The result shows that ultimate load carrying capacity of reinforced concrete beams and load at first crack decreases with the raise in temperatures and increased percentage of RCA content in the mix. Further that 100% RCA replacement specimens showed lesser cracks when compared to the other mixes and the inclusion of fibres enhances the flexural capacity of members highlighting the importance of fibres.

RCA can be used for structural purposes and the study can be projected for assessing the performance of real structures with the extent of fire damage when recycled aggregates are used.

Most of recycled materials can be used in the regular concrete which solves two problems namely avoiding the dumping of C&D waste and preventing the usage of natural aggregates. Hence the study provides sustainable option for the production of concrete.

The reduction in capacity of flexural members due to the utilisation of recycled aggregates can be negated by the usage of fibres. Hence improved flexural performance is observed for specimens with fibres at sustained elevated temperatures.