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Is customer service getting worse? Earlier this year Gordon Simmons Research, in association with Management & Marketing Development Ltd, interviewed a representative national sample of 1,007 adults aged 16 years and over. These adults were asked which retail types they had visited in the last four weeks and whether they had any complaints about the service received on any of their visits. The research was concerned with problems at the point of sale rather than after‐sales service. Martin Simmons' conclusion is that customer service standards are going to get worse before they get better, and that any retailer who can demonstrate a competitive edge in service levels and staff training could more than pay for his investment through higher sales and profits.

Decline in consumer demand and severe pressure on costs are — not surprisingly — the two aspects of the recession which, according to a survey by Gordon Simmons Research, are hitting retailers most hard. In the immediate future, the overall pattern indicates an increase in store investment and improvement to compensate for the slowing down in recent years. And of course there will be growing emphasis on larger units, and the continued growth of credit. This article is based on personal interviews conducted by GSR executives, during November and December 1980, with top management in 12 major retail organisations (listed at the end of this article). These retailers, although few in number, represent a high proportion of retail turnover because of the concentration of the trade. They cover a wide cross‐section of retailing: supermarkets, department stores, electrical goods outlets, variety stores, men's and women's fashion. The survey examined these retailers' reactions to the recession, the effect of the economic climate on their policies, and likely retail developments in the 1980s.

In 1980 Gordon Simmons Research, in association with M & MD, interviewed a cross‐section of top management at 12 major retail organisations to examine their reactions to the recession and the likely effect of the economic climate on their policies throughout the 1980s (RDM, May/June 1981, p.10). This article is based on an update conducted two years later during August and September 1982, with the same organisations. These retailers, though few in number, represent a high proportion of retail turnover because of the concentration of trade. They cover a wide cross‐section of retailing; supermarkets, department stores, electrical goods outlets, variety stores, men's and women's fashion. Interestingly enough, the interviews in this second survey coincided almost exactly with the beginning of a marked increase in consumer expenditure which began in the third quarter of 1982 (RDM, November/December 1982, p.4), and which has persisted up to the time of writing. However, the responses from retailers discussed in this article relate mostly to their experience through 1981 and 1982.

More attention is now being devoted to the contribution which market research can make to the location, development and appraisal of individual stores. This is a result of trends in European retailing where stores are generally built much larger, where they sell a greater variety of merchandise and attract people from wider distances. In the following pages, Mr Simmons assesses the new role of market research, and in particular, what it can tell the retailer about his image, so important when competing for custom in an out‐of‐town shopping centre.

The purpose of this study is to extend Bippus and Young’s (2005) study and examine the effectiveness of the “I-you,” “I,” “You,” “We,” “But” and Question-based “Why” statements from Winer’s (2021) verbal coding program of conflict management using Bandura’s (1977) social learning theory (SLT).

Mixed methods were used using 175 university students from Texas and New York. A cross-sectional convenience sampling approach was conducted. Survey data was collected using Qualtrics.

Descriptive results demonstrated that the “We” statement was the most passive, the “I-you” statement was the most assertive and the “But,” “I,” “You” and Question statements were perceived to be aggressive. In addition, assertive “I-You” statements were perceived to be more effective in resolving the conflict and maintaining a relationship, whereas aggressive statements were less likely to resolve the conflict and maintain the relationship. Qualitative themes also support the “I-You” statement as the most assertive, while the “But,” “You” and “I” statements were found to be the most aggressive statements.

Implications and applications are discussed to stimulate future research among researchers and practitioners when addressing conflict. Being aware of the verbal statements that de-escalate conflict may be helpful in solving conflict in interpersonal, family and professional relationships. Future trainings can adopt effective verbal statements to resolve conflict when experiencing anger issues. Future research can continue to investigate verbal communication statements using SLT to help practitioners and managers address conflict in interpersonal relationships.

This study examines verbal statements in relation to communication styles and conflict management.

We have a mere handful of large‐scale mass merchandisers in this country; of these the leading company is undoubtedly the northern‐based group Asda, whose financial performance since its inception in 1965 has been little short of spectacular. At the April 1973 year end, working from 1.2m sq ft of selling space, it notched up figures of £6.24m pre‐tax profit on a turnover of £128m. This feature describes the group's merchandising policies, its emphasis on sound location and the importance it attaches to rationalised distribution systems.

Meckler Publishing has announced the acquisition of Micro Software Reports and Micro Software Evaluations from Nolan Information Management Services of Torrance, California. Alan M. Meckler, President of Meckler Publishing, stated that “Micro Software Reports is the world's largest and most comprehensive index to microcomputer software with specific library applications”. He went on to say that “the publication indexes 110 library and computer oriented journals concentrating on information that includes pricing, installation locations and complete system descriptions”.

This study develops a computational method to investigate the predominant language styles in political discussions on Twitter and their connections with users' online characteristics.

This study gathers a large Twitter dataset comprising political discussions across various topics from general users. It utilizes an unsupervised machine learning algorithm with pre-defined language features to detect language styles in political discussions on Twitter. Furthermore, it employs a multinomial model to explore the relationships between language styles and users' online characteristics.

Through the analysis of over 700,000 political tweets, this study identifies six language styles: mobilizing, self-expressive, argumentative, narrative, analytic and informational. Furthermore, by investigating the covariation between language styles and users' online characteristics, such as social connections, expressive desires and gender, this study reveals a preference for an informational style and an aversion to an argumentative style in political discussions. It also uncovers gender differences in language styles, with women being more likely to belong to the mobilizing group but less likely to belong to the analytic and informational groups.

This study provides insights into the psychological mechanisms and social statuses of users who adopt particular language styles. It assists political communicators in understanding their audience and tailoring their language to suit specific contexts and communication objectives.

This study reveals gender differences in language styles, suggesting that women may have a heightened desire for social support in political discussions. It highlights that traditional gender disparities in politics might persist in online public spaces.

This study develops a computational methodology by combining cluster analysis with pre-defined linguistic features to categorize language styles. This approach integrates statistical algorithms with communication and linguistic theories, providing researchers with an unsupervised method for analyzing textual data. It focuses on detecting language styles rather than topics or themes in the text, complementing widely used text classification methods such as topic modeling. Additionally, this study explores the associations between language styles and the online characteristics of social media users in a political context.

In an effort to win back consumer spending that is increasingly being diverted into areas not covered by the retail sector, such as housing, cars, entertainment and holidays, it is imperative that shops develop a clear and winning formula to retrieve the capricious shopper. The task is made harder by the growing competition in the retail sector itself and by the more sophisticated, discerning and demanding nature of today's potential customers. At a one‐day conference, “Retail Strategies for the 1980s”, organised by Mintel Publications and which took place at the Barbican Centre, London, in June, a wide group of retailers gave presentations outlining their strategy options and evaluating their prospects for success. RDM was there.

Social media have increasingly gained credibility as information sources in emergencies. Retweeting or resharing nature has made Twitter a popular medium of information dissemination. The purpose of this article is to enhance our understanding of both linguistic style and content properties (i.e. both affective and informational contents) that drives resharing behavior or virality of disaster messages on Twitter. We investigate this issue in the context of natural disaster crisis.

In this study, the authors develop, drawing upon language expectancy and uncertainty reduction theories as an enabling framework, hypotheses about how the language (i.e. style and content) influence resharing behavior. They employ a natural language processing of disaster tweets to examine how the language – linguistic style (concrete and interactive language) and linguistic content (information- and affect-focused language) – affects resharing behavior on Twitter during natural disasters. To examine the effects of both linguistic style and content factors on virality, a series of negative binomial regressions were conducted, particularly owing to the highly skewed count data.

Our analysis of tweets from the 2013 Colorado floods shows that resharing disasters tweets increases with the use of concrete language style during acute emergencies. Interactive language is also positively associated with retweet frequency. In addition, neither positive nor negative emotional tweets drive down resharing during acute crises, while information-focused language content has a significantly positive effect on virality.

Agencies for public safety and disaster management or volunteer organizations involved in disseminating crisis and risk information to the public may leverage the impacts of the linguistic style and language content through the lens of our research model. The findings encourage practitioners to focus on the role of linguistic style cues during acute disasters. Specifically, from the uncertainty reduction perspective, using concrete language in the disaster tweets is the expected norm, leading to a higher likelihood of virality. Also, interactively frame disaster tweets are more likely to be diffused to a larger number of people on Twitter.

The language that people use offer important psychological cue to their intentions and motivations. However, the role of language on Twitter has largely been ignored in this crisis communication and few prior studies have examined the relationship between language and virality during acute emergencies. This article explains the complex and multifaceted nature of information resharing behavior using a multi-theoretical approach – including uncertainty reduction and language expectancy theory – to understand effects of language style and content cues on resharing behavior in the context of natural crisis events.