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This study examines the effect of employees' perceptions of political connections on performance measurement systems (PMS) design choice and firm performance. In addition, this study explores the moderating effect of social networking, a very common and widely used factor by domestic and foreign multinational firms operating in China, and its joint effect with political connections or PMS design choice on firm performance. We collected survey responses from a sample of 110 managers from manufacturing firms in China. Our results reveal that highly politically connected managers use nonfinancial measures, leading to improved firm performance. Our results suggest that social networking interacts significantly with political connections, and nonfinancial and financial measures on firm performance. The theoretical and practical implications of our findings are discussed.

Twitter is gaining popularity as a microblogging and social networking service to discuss various social issues. Coronavirus disease 2019 (COVID-19) has become a global pandemic and is discussed worldwide. Social media is an instant platform to deliberate various dimensions of COVID-19. The purpose of the study is to explore and analyze the public sentiments related to COVID-19 vaccines across the Twitter messages (positive, neutral, and negative) and the impact tweets make across digital social circles.

To fetch the vaccine-related posts, a manual examination of randomly selected 500 tweets was carried out to identify the popular hashtags relevant to the vaccine conversation. It was found that the hashtags “covid19vaccine” and “coronavirusvaccine” were the two popular hashtags used to discuss the communications related to COVID-19 vaccines. 23,575 global tweets available in public domain were retrieved through “Twitter Application Programming Interface” (API), using “Orange Software”, an open-source machine learning, data visualization and data mining toolkit. The study was confined to the tweets posted in English language only. The default data cleaning and preprocessing techniques available in the “Orange Software” were applied to the dataset, which include “transformation”, “tokenization” and “filtering”. The “Valence Aware Dictionary for sEntiment Reasoning” (VADER) tool was used for classification of tweets to determine the tweet sentiments (positive, neutral and negative) as well as the degree of sentiments (compound score also known as sentiment score). To assess the influence/impact of tweets account wise (verified and unverified) and sentiment wise (positive, neutral, and negative), the retweets and likes, which offer a sort of reward or acknowledgment of tweets, were used.

A gradual decline in the number of tweets over the time is observed. Majority (11,205; 47.52%) of tweets express positive sentiments, followed by neutral (7,948; 33.71%) and negative sentiments (4,422; 18.75%), respectively. The study also signifies a substantial difference between the impact of tweets tweeted by verified and unverified users. The tweets related to verified users have a higher impact both in terms of retweets (65.91%) and likes (84.62%) compared to the tweets tweeted by unverified users. Tweets expressing positive sentiments have the highest impact both in terms of likes (mean = 10.48) and retweets (mean = 3.07) compared to those that express neutral or negative sentiments.

The main limitation of the study is that the sentiments of the people expressed over one single social platform, that is, Twitter have been studied which cannot generalize the global public perceptions. There can be a variation in the results when the datasets from other social media platforms will be studied.

The study will help to know the people's sentiments and beliefs toward the COVID-19 vaccines. Sentiments that people hold about the COVID-19 vaccines are studied, which will help health policymakers understand the polarity (positive, negative, and neutral) of the tweets and thus see the public reaction and reflect the types of information people are exposed to about vaccines. The study can aid the health sectors to intensify positive messages and eliminate negative messages for an enhanced vaccination uptake. The research can also help design more operative vaccine-advocating communication by customizing messages using the obtained knowledge from the sentiments and opinions about the vaccines.

The paper focuses on an essential aspect of COVID-19 vaccines and how people express themselves (positively, neutrally and negatively) on Twitter.

The purpose of this study is to improve the tribological characteristics of cotton-biolubricant by adding nanoparticles at extreme pressure (EP) conditions in comparison with commercial lubricant SAE-40.

This research involved the synthesis of cotton-biolubricant by transesterification process and then the addition of nanoparticles in it to improve anti wear (AW)/EP tribological behavior. SAE-40 was studied as a reference commercial lubricant. AW/EP characteristics of all samples were estimated by the four-ball tribo-tester according to the American Society for Testing and Materials D2783 standard.

The addition of 1-Wt.% TiO₂ and Al₂O₃ with oleic acid surfactant in cotton-biolubricant decreased wear scar diameter effectively and enhanced the lubricity, load-wear-index, weld-load and flash-temperature-parameters. This investigation revealed that cotton-biolubricant with TiO₂ nano-particle additive is more effective and will help in developing new efficient biolubricant to replace petroleum-based lubricants.

Cotton biolubricant with TiO₂ nano-particles appeared as an optimistic solution for the global bio-lubricant market.

No one has not studied the cotton biolubricant with nanoparticles for internal combustion engine applications at high temperature and EP conditions.

Sharing and obtaining information over social media has enabled people to express their opinions regarding any event. Since the tweets regarding the Russia-Ukraine war were extensively publicized on social media, this study aims to analyse the temporal sentiments people express through tweets related to the war.

Relevant hashtag related to the Russia-Ukraine war was identified, and tweets were downloaded using Twitter API, which were later migrated to Orange Data mining software. Pre-processing techniques like transformation, tokenization, and filtering were applied to the extracted tweets. VADER (Valence Aware Dictionary for Sentiment Reasoning) sentiment analysis module of Orange software was used to categorize tweets into positive, negative and neutral ones based on the tweet polarity. For ascertaining the key and co-occurring terms and phrases in tweets and also to visualize the keyword clusters, VOSviewer, a data visualization software, was made use of.

An increase in the number of tweets is witnessed in the initial days, while a decline is observed over time. Most tweets are negative in nature, followed by positive and neutral ones. It is also ascertained that tweets from verified accounts are more impactful than unverified ones. russiaukrainewar, ukraine, russia, false, war, nato, zelensky and stoprussia are the dominant co-occurring keywords. Ukraine, Russia and Putin are the top hashtags for sentiment representation. India, the USA and the UK contribute the highest tweets.

The study tries to explore the public sentiments expressed over Twitter related to Russia-Ukraine war.

Summarizes previous research on financial analysts’ forecasts and the segmentation of international finance markets. Hypothesizes that the accuracy of earnings forecasts in a country is negatively related to the country return, and positively to the country risk. Uses 1992‐94 data from 12 countries to test this, supports the hypothesis and calls for further research.

In the study, a five-dimensional-safety risk assessment model (5D-SRAM) is developed to improve the construction safety risk assessment approaches available in the literature. To that purpose, a hybrid multi-dimensional fuzzy-based model is proposed, which provides a comprehensive ranking system for the safety risks existing in a project by considering the contextualization of the construction-related activities resulting in an accident.

The developed 5D-SRAM is based on an amalgamation of different fuzzy-based techniques. Through the proposed fuzzy analytic hierarchy process (AHP) method, the importance weights of essential risk dimensions playing role in defining the magnitude of the construction-related risks are obtained, while a precise prioritized ranking system for the identified safety risks is acquired using the proposed fuzzy technique of order preference similarity to the ideal solution (FTOPSIS).

Through the application of the proposed 5D-SRAM to a real-life case study – which is the case of green building construction projects located in Hong Kong – contributions are realized as follows: (1) determination of a more complete range of risk dimensions, (2) calculation of importance weightings for each risk dimension and (3) obtainment of a precise and inclusive ranking system for safety risks. Additionally, the supremacy of the developed 5D-SRAM against the other safety assessment approaches that are commonly adopted in the construction industry is proved.

The developed 5D-SRAM provides the concerned safety decision-makers with not only all the crucial dimensions that play roles toward the magnitude of safety risks posing threats to the workers involved in construction activities, but also they are given hindsight regarding the importance weights of these dimensions. Additionally, the concerned parties are embellished with the final ranking of safety risks in a more comprehensive way than those of existing assessment methods, leading to sagacious adoption of future prudent strategies for dealing with such risks occurring on construction sites.

Numerous studies have documented the safety risks faced by construction workers including proposals for risk assessment models. However, the dimensions considered by such models are limited, generally constrained to risk event probability combined with risk impact severity. Overlooking other dimensions that are essential towards the calculation of safety risks' magnitude culminates in overshadowing the further adoption of fruitful mitigative actions. To overcome this shortcoming, this study proposes a novel 5D-SRAM.

The paper investigates whether firms’ exposure to information security risk influences firms’ costs of capital. Most IT firms highly rely on computer systems and network appliances; it may cause disasters if firms are involved in great information security risk. In the sample of Taiwan’s semiconductor firms during 2005–2016, we show that ISO 27001-certified firms (a well-known information security certificate) have lower costs of debt, but whether firms are ISO 27001-certified is not associated with firms’ costs of equity. Our findings are consistent with modern financial theories: debt holders, as put writers to firms’ value, benefit from firms’ lower information security risk, and better corporate governance, and thus lower firms’ costs of debt. On the other hand, equity holders should hold efficient portfolio through diversification and thus firms’ costs of equity should not be influenced by firms’ information security risk, which belongs to idiosyncratic risk in the portfolio theory.

Global brands have become increasingly vulnerable to external disruptions that have negative spillover effects on consumers, business and brands. This research area has recently garnered interest post-pandemic yet remains fragmented. The purpose of this paper is to recognize the most impactful exogenous brand crisis (EBC) and its affective and behavioural impact on consumers.

In Study 1, we applied repertory grid technique (RGT), photo elicitation method and ANOVA comparisons, to identify the most significant EBC, in terms of repercussions on consumer purchases. In Study 2, we performed collage construction and content analysis to ascertain the impact of the identified significant crisis (from Study 1) on consumer behaviour in terms of affective and behavioural changes.

Study 1 results reveal Spread-of-diseases and Natural disaster to be the most impactful EBC based on consumer’s purchase decisions. Study 2 findings uncover three distinct themes, namely, deviant demand, emotional upheaval and community bonding that throws light on the affective and behavioural changes in consumer behaviour during the two significant EBC events.

The collated results of the two studies draw insights towards understanding the largely unexplored conceptualisation of EBC from a multi-level (micro-meso-macro) perspective. The integrated framework drawn, highlight the roles and influences of different players in exogenous brand crisis management and suggests future research agendas based on theoretical underpinnings.

To the best of our knowledge, this is the first study which identifies the most important EBC and explicates its profound impact on consumer purchase behaviour, providing critical insights to brand managers and practitioners to take an inclusive approach towards exogenous crises.

The purpose of this paper is to explore consumers’ retailer preferences during economic growth and recession periods in a Muslim-intensive country, and to compare the efficiency of retailers of different formats.

The data of the retailers operating in different formats in the first two quarters of 2018–2020 are used in the study. The data are analyzed by using Data Envelopment Analysis (DEA). The inputs of the DEA model are personnel expenses, rent costs and advertising expenses; and the outputs are sales and profits, which are the main objective of businesses. Because of the structure of the data, the non-oriented approach is used. The efficiency of retailers is determined in the study with super efficiency, which allows retailers to rank their productivity.

Findings of study present that consumers exhibited price-oriented behaviors during economic recession periods. DEA findings shows that discount stores are the most efficient retailers. However, study findings also reveal that retailers who support cost-reduction strategies with promotion activities are more efficient than others during economic recession periods.

Recommendations are made for the decision makers of the retailers in line with the findings of the study.

The study contributes to the literature by evaluating the consumer preferences and the efficiency of retailers in COVID-19 outbreak period, which is one of the most special periods in world history.

The work set out to design and develop an overheating risk tool using the UKCP09 climate projections that is compatible with building performance simulation software. The aim of the tool is to exploit the Weather Generator and give a reasonably accurate assessment of a building's performance in future climates, without adding significant time, cost or complexity to the design team's work.

Because simulating every possible future climate is impracticable, the approach adopted was to use principal component analysis to give a statistically rigorous simplification of the climate projections. The perceptions and requirements of potential users were assessed through surveys, interviews and focus groups.

It is possible to convert a single dynamic simulation output into many hundreds of simulation results at hourly resolution for equally probable climates, giving a population of outcomes for the performance of a specific building in a future climate, thus helping the user choose adaptations that might reduce the risk of overheating. The tool outputs can be delivered as a probabilistic overheating curve and feed into a risk management matrix. Professionals recognized the need to quantify overheating risk, particularly for non‐domestic buildings, and were concerned about the ease of incorporating the UKCP09 projections into this process. The new tool has the potential to meet these concerns.

The paper is the first attempt to link UKCP09 climate projections and building performance simulation software in this way and the work offers the potential for design practitioners to use the tool to quickly assess the risk of overheating in their designs and adapt them accordingly.