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While prior research provides interesting insights into the effect of social media use in enterprises, there is limited research on how use of different social media platforms affects employee job satisfaction and work efficiency. This study developed a research model to investigate how public and private social media platforms used for different motivations affect employee job satisfaction and work efficiency.

Online surveys were conducted in China, generating 453 valid responses for analysis. Structural equation modeling is performed to test the research model and hypotheses.

The results suggest that (1) public social media used for both work- and social-related motivations positively affects employee job satisfaction, while private social media only used for social-related motivations can contribute to employee job satisfaction. (2) Public and private social media used for work-related motivations can contribute to employee work efficiency, while social-related motivations for use of public and private social media and employee work efficiency are not significant. (3) In the process of social media usage influencing employee job satisfaction and work efficiency, employees of different genders show significant differences.

First, this paper contributes to information systems social media research by examining the joint effects of different motivations for public and private social media usage on employee job satisfaction and work efficiency in organizations. Second, it contributes to uses and gratification theory by clarifying the relationship between different motivations for enterprise social media use and its needs.

This paper evaluates the working capital management (WCM) efficiency of the Indian manufacturing industries through data envelopment analysis (DEA) and empirically investigates the influence of several exogenous variables on the WCM efficiency.

WCM efficiency was calculated using BCC input-oriented DEA model. Further, the panel data fixed effect model was used on a sample of 1391 Indian manufacturing firms spread across nine industries, covering the period from 2008 to 2019.

Firstly, the WCM efficiency of Indian manufacturing industries has been stable over the analysis period. Secondly, the capacity to generate internal resources, size, age, productivity, gross domestic product and interest rate significantly influence WCM efficiency.

First, the selected study period has observed various economic uncertainties including demonetization and recession, so the scenario might differ in normal conditions or country-wise. Second, the findings might not be generalizable to the developed economies, since the current study sample belongs to a developing economy, which further provides scope for comparative study.

An efficient model for managing the working capital comprising most vital determinants could enhance the firms' valuation and goodwill. Also, this study would be helpful for financial executives, manufacturers, policymakers, investors, researchers and other stakeholders.

This study estimates the industry-wise WCM efficiency of the Indian manufacturing sector and suggests measures to the concerned parties on areas to focus on and provide evidence on the estimated relationships of firm-level and macroeconomic determinants with WCM efficiency.

This study develops an integrated approach combining data envelopment analysis (DEA) and structural equation modeling (SEM) for estimating the working capital management (WCM) efficiency and evaluating the effects of diverse exogenous variables on the WCM efficiency and firms' performance.

DEA is applied for deriving WCM efficiency for 212 Indian manufacturing firms over a period from 2008 to 2019. Also, the effect of human capital (HC), structural capital (SC), cost of external financing (CEF), interest coverage (IC), leverage (LEV), net fixed asset ratio (NFA), asset turnover ratio (ATR) and productivity (PRD) on the WCM efficiency and firms' performance is examined using SEM.

The average mean efficiency scores ranging from 0.623 to 0.654 highlight the firms operating at around 60% of WCM efficiency only, which is a major concern for Indian manufacturing firms. Further, IC, LEV, NFA, ATR revealed direct effect on the WCM efficiency as well as indirect effect on firms' performance, whereas CEF had only a direct effect on WCM efficiency. HC, SC and PRD had no effects on WCM efficiency and firms' performance.

The findings offer vital insights in guiding policy decisions for Indian manufacturing firms.

This study is the first to identify the endogenous nature of the relationship of HC, SC, CEF, IC altogether with firms' performance, compounded by the WCM efficiency, by applying a comprehensive methodology of DEA and SEM and provides an efficiency performance model for better decision-making.

The purpose of this study is to get insights into working capital management (WCM) practices and the determinants of its efficiency prevailing in the Indian manufacturing sector using firm-specific as well as macro-economic variables by examining three efficiency models, i.e. cash conversion cycle (CCC), cash conversion efficiency (CCE) and net working capital level (NWCL).

The study uses panel data techniques on 1,207 firms of the Indian manufacturing sector, as well as on its nine key manufacturing industries from 2008 to 2018 for the analysis.

Several firm-specific variables such as net fixed asset ratio, size of the firm, profitability, firm’s growth, asset turnover ratio, age of the firm, interest rate and leverage have significant effect on WCM efficiency, whereas total assets growth rate, gross domestic product growth rate and inflation rate have insignificant effect on WCM efficiency.

The study provides new empirical evidence on the short-term liquidity management of manufacturing firms prevailing in the developing countries such as India. The findings are particularly relevant in the present scenario when the liquidity levels are decelerating and there is a marked slowdown in private credit flows to the manufacturing sector due to the problem of burgeoning non-performing assets.

This study examines WCM efficiency exhaustively by incorporating both firm-specific and macro-economic variables using three efficiency measures, i.e. CCC, CCE and NWCL, results of which emerged as an answer to an efficient WCM.

The purpose of this study is to introduce working capital efficiency multiplier (WCEM) as a direct profitability measure of working capital management. The existing accounting measures in the literature establish an indirect approach to study the relationship between working capital efficiency and profitability of the firms.

Using the help of a set of companies from CMIE Prowess database, the study introduces WCEM as a direct profitability measure of working capital efficiency.

In this study, a new direct measure of working capital efficiency is introduced which is multiplicative in nature. WCEM is a product of three components, namely, WACC, ratio of the sum of trade receivables and inventories to trade payables and ratio of net working capital (NWC) to net sales.

The importance of direct measure like WCEM could be enormous in performance evaluation of a firm. It can be used as an indicator for choosing a suitable investment opportunity by an investor. This is due to the fact that the firm that is highly efficient in managing working capital is less exposed to liquidity risk. At the same time, the firm is less dependent on external financing. Therefore, such firms eventually create more value for their shareholders. Another indication that WCEM provides is to gauge the bargaining power of the firm and its competitive position in the market. Lower WCEM indicates higher bargaining power of a firm across the value chain, and its superior position relative to its competitors.

Most of the studies on WCM are of the empirical type and there is a complete dearth on theoretical framework. Researchers hereafter can consider WCEM as one of the financial performance variables in place of the existing measures such as return on asset (ROA), return on invested capital (ROIC), return on equity (ROE), gross operating income (GOI) and net operating income (NOI) and thereby can contribute new empirical insights through their research outcomes.

The purpose of this paper is to empirically investigate the relationship between working capital management (WCM) efficiency and exogenous variables of the Indian manufacturing sector along with its sub-industries that are involved in export activities.

Panel regression (fixed effects) was used on a sample of 563 Indian manufacturing firms involved in export activities, covering a time period from 2008 to 2018.

Industry-wise results showed a significant relation of leverage, net fixed asset ratio, profitability, asset turnover ratio, total asset growth rate and productivity with cash conversion cycle (CCC).

Firstly, having taken a sample from a developing economy, the results of our study may be generalizable only among developing contexts. Secondly, the time period taken in this study (2008–2018) has witnessed several economic fluctuations such as recession and demonetization which might differ for the firms or countries in normal conditions.

An improved working capital model could advance the firms' performance by reducing the CCC of the firm, thereby creating efficiency in WCM. In addition, the results of this study could be helpful for many stakeholders such as working capital managers, debt holders, investors, financial consultants and others for monitoring the firms.

This study contributes to the existing literature in the relation between WCM efficiency and exogenous variables of the Indian manufacturing firms engaged in the export activities. Moreover, this study is one of the few research studies to investigate this relationship among Indian export firms in different industries, thus filling the gap in similar work done in other countries.

The main aim of the paper is to establish the effects of appropriately organized work as well as the effects of the employees' concerns related to work during the COVID-19 pandemic on work efficiency and work satisfaction among employees working from home during this period. The empirical research includes 619 employees in Slovenia, who participated in the survey during the COVID-19 pandemic.

Structural equation modeling was used in exploring the effects between constructs.

Based on the results, the authors found that appropriately organized work during the COVID-19 pandemic has a positive effect not only on the work efficiency of employees who work from home during the COVID-19 pandemic in Slovenia but also on their work satisfaction. Also, based on the results, the authors found that the employees' concerns related to work during the COVID-19 pandemic have a negative effect on the work efficiency and on the work satisfaction of employees who work from home during this period in Slovenia.

The COVID-19 pandemic dramatically changed the way we live and work; therefore, this paper contributes to the creation of new working conditions and employee management during and also after the COVID-19 pandemic.

The purpose of this study is to investigate the impact of corporate governance on working capital management efficiency. This study also seeks to extend the findings of Gill and Shah.

This study applied a co‐relational research design. A sample was selected of 180 American manufacturing firms listed on the New York Stock Exchange (NYSE) for a period of 3 years (from 2009‐2011).

The findings of this study indicate that corporate governance plays some role in improving the efficiency of working capital management.

This is a co‐relational study that investigated the association between corporate governance and working capital management efficiency. There is not necessarily a causal relationship between the two, although the paper provides some conjectures to the findings. The findings of this study may only be generalized to firms similar to those that were included in this research.

This study contributes to the literature on the factors that improve the efficiency of working capital management, and in particular on the association between several features of corporate governance and the efficiency of working capital management. The findings may be useful for financial managers, investors, financial management consultants, and other stakeholders.

This study aims to assess the efficiency of managing working capital in 1,388 Indian manufacturing firms from 2008 to 2019 and investigate the effects of firm-specific and macro-level determinants on working capital management (WCM) efficiency.

The current study accommodates a slack-based measure (SBM) in data envelopment analysis (DEA) for computing WCM efficiency. Further, we implement a panel data fixed-effects model that controls for heterogeneity across firms in determining the relationships of selected variables with WCM efficiency.

The results highlight that manufacturing firms operate at around 50 percent efficiency, which is constant throughout the study period. Furthermore, among the selected variables, yield, earnings, age, size, ability to create internal resources, interest rate and gross domestic product (GDP) significantly affect WCM efficiency.

Instead of the traditional models used for assessing efficiency, the SBM-DEA model is unit-invariant and monotone for slacks, implying that it can handle zero and negative data, which overcomes the incapability of prior DEA models. Hence, this provides accurate efficiency scores for robust analysis. Additionally, this paper provides a holistic working capital model recognizing firm-specific and macro-level determinants for a more explicit estimation of the relationship between WCM efficiency and the selected determinants.