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This study investigates organizational climate under the thriving at work perspective using a network approach. The authors demonstrate how organizational climate functions as a complex system and what relationships between variables from different dimensions are the most important to characterize the construct.

By surveying 119,266 workers from 284 companies based in Brazil, the authors estimated a Gaussian graphical model with LASSO regularization for the complete dataset and for two subsets of cases randomly drawn from the whole dataset. The walktrap algorithm was applied for community detection, and a strong model for measurement invariance was fit to test whether the organizational climate is perceived similarly across groups.

Results show that the networks estimated for both groups are quite consistent, with similar number of communities and items detected. The same pattern was found for the expected influence of each item. Measurement invariance was confirmed, showing that organizational climate is perceived similarly in both groups. The most important community detected and whose items have higher levels of centrality was organizational commitment, followed by a community centered around macro-organizational aspects covering cultural integrity, organizational agility and responsible leadership.

Studies in the field have attested to the possibility of investigating the phenomenon from four (Campbell et al., 1970) to over 80 dimensions (Koys and DeCottis, 1991). As a result, since several dimensions have been produced to investigate organizational climate, there is no consensus on the quality and number of dimensions that should be considered to measure such a vast and multifaceted construct. Built on thriving at work perspective, eight dimensions were devised to cover a wide range of characteristics that distinguish organizational climate, including those related to Industry 4.0 (Coetzee, 2019). However, one may argue that a few dimensions, namely social responsibility, diversity and inclusion, or even more items describing work-life balance could expand the depth and breadth of the instrument and potentially trigger new associations that might eventually impose a new logic to the comprehension of climate as a system. Future studies combining the dimensions investigated in this study with other dimensions are therefore highly recommended for an even more comprehensive investigation.

The results of this investigation show how to apply psychological networks to gain insights into different variables and dimensions of organizational climate. These findings can be used for the development of organizational policies focused on the most relevant aspects of organizational climate. This information would allow organizations to go beyond simply describing the individual frequencies for each item and could even be used to create a weighted scoring model that could prioritize variables with higher levels of centrality.

To the authors’ knowledge, this is the first study that investigates organizational climate using psychological networks; it provides a better understanding of the relationships established between items from different dimensions as opposed to the common cause framework whose focus is on the investigation of dimensions separately.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Dimensions of organizational climate vary in their influence of how workers perceive the firm. Adopting an approach which combines psychological networks analysis and Thriving at Work constructs can help practitioners ascertain which dimensions have greatest scope to increase the level of organizational commitment among employees.

The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

Lean healthcare (LHC) applies lean philosophy in the healthcare sector to promote a culture of continuous improvement through the elimination of non-value-added activities. Studies on the subject can be classified as conceptual (theoretical) or analytical (applied). Therefore, this research compares bibliometric indicators between conceptual and analytical articles on LHC.

For data collection, the PRISMA Protocol was employed, and 488 articles published from 2009 to 2021, indexed in the Scopus and WoS databases, were retrieved.

This study reveals how conceptual and analytical LHC studies are organized in terms of the most relevant journals, articles, institutions, countries, the total number of citations, collaboration networks (co-authorship, international collaboration network and institutional collaboration network) and main co-words.

Only four papers conducting bibliometric analysis on LHC studies were identified in the Scopus and Web of Science databases. In addition, none of these papers compared conceptual and analytical bibliometric indicators to reveal the evolution, organization and trends of each category. Therefore, this work is not only the first to make this comparison but also the first to analyze the collaboration between authors, institutions and countries in relation to studies on LHC. The analyses performed in this work allow one new possible understanding, by researchers and health professionals, of the literature behavior in this field of study.

This teaching case aims to provide in-class discussions on the commercialization and consumption of goods in spiritual markets. This teaching case is a narrative based on facts with a fictitious plot reporting the journeys of the launch, commercialization and consumption of mineral water in bottles in the shape of Father Cícero – a religious leader in Northeast Brazil – produced by Blue Spring Mineral Water in Juazeiro do Norte’s pilgrimage spiritual market.

Primary and secondary data sources were gathered. Two focus groups with pilgrims and semi-structured interviews with Blue Spring leaders and a local Church representative were conducted as primary data. As secondary data, a dossier was created holding content from newspapers and blogs online on the focal product and data from the company’s official website and social networks.

Throughout the case, the strategies and challenges of the production and commercialization of this religiously appealing product and the consumer practices adopted by different consumer profiles are unfolded.

This case intends to be a useful pedagogical tool to discuss the creation, production, commercialization and consumption of goods in spiritual markets. The case allows students to experience Blue Spring’s managers’ point of view regarding the decisions of production and commercialization of the focal product. In a broad sense, this case intends to inform future marketers of the importance of balancing commercialization in religious contexts.

Social media networks like Twitter, Facebook, WhatsApp etc. are most commonly used medium for sharing news, opinions and to stay in touch with peers. Messages on twitter are limited to 140 characters. This led users to create their own novel syntax in tweets to express more in lesser words. Free writing style, use of URLs, markup syntax, inappropriate punctuations, ungrammatical structures, abbreviations etc. makes it harder to mine useful information from them. For each tweet, we can get an explicit time stamp, the name of the user, the social network the user belongs to, or even the GPS coordinates if the tweet is created with a GPS-enabled mobile device. With these features, Twitter is, in nature, a good resource for detecting and analyzing the real time events happening around the world. By using the speed and coverage of Twitter, we can detect events, a sequence of important keywords being talked, in a timely manner which can be used in different applications like natural calamity relief support, earthquake relief support, product launches, suspicious activity detection etc. The keyword detection process from Twitter can be seen as a two step process: detection of keyword in the raw text form (words as posted by the users) and keyword normalization process (reforming the users’ unstructured words in the complete meaningful English language words). In this paper a keyword detection technique based upon the graph, spanning tree and Page Rank algorithm is proposed. A text normalization technique based upon hybrid approach using Levenshtein distance, demetaphone algorithm and dictionary mapping is proposed to work upon the unstructured keywords as produced by the proposed keyword detector. The proposed normalization technique is validated using the standard lexnorm 1.2 dataset. The proposed system is used to detect the keywords from Twiter text being posted at real time. The detected and normalized keywords are further validated from the search engine results at later time for detection of events.