Enhancing operations management through smart sensors: measuring and improving well-being, interaction and performance of logistics workers

Purpose The purpose of the research is to conduct an exploratory investigation of the material handling activities of an Italian logistics hub. Wearable sensors and other smart tools were used for collecting human and environmental features during working activities. These factors were correlated with workers' performance and well-being. Design/methodology/approach Human and environmental factors play an important role in operations management activities since they significantly influence employees' performance, well-being and safety. Surprisingly, empirical studies about the impact of such aspects on logistics operations are still very limited. Trying to fill this gap, the research empirically explores human and environmental factors affecting the performance of logistics workers exploiting smart tools. Findings Results suggest that human attitudes, interactions, emotions and environmental conditions remarkably influence workers' performance and well-being, however, showing different relationships depending on individual characteristics of each worker. Practical implications The authors' research opens up new avenues for profiling employees and adopting an individualized human resource management, providing managers with an operational system capable to potentially check and improve workers' well-being and performance. Originality/value The originality of the study comes from the in-depth exploration of human and environmental factors using body-worn sensors during work activities, by recording individual, collaborative and environmental data in real-time. To the best of the authors' knowledge, the current paper is the first time that such a detailed analysis has been carried out in real-world logistics operations.

Put your money where your mouth is: Using deep learning to identify consumer tribes from word usage

Internet and social media offer firms novel ways of managing their marketing strategy and gain competitive advantage. The groups of users expressing themselves on the Internet about a particular topic, product, or brand are frequently called a virtual tribe or E-tribe. However, there are no automatic tools for identifying and studying the characteristics of these virtual tribes. Towards this aim, this paper presents Tribefinder, a system to reveal Twitter users' tribal affiliations, by analyzing their tweets and language use. To show the potential of this instrument, we provide an example considering three specific tribal macro-categories: alternative realities, lifestyle, and recreation. In addition, we discuss the different characteristics of each identified tribe, in terms of use of language and social interaction metrics. Tribefinder illustrates the importance of adopting a new lens for studying virtual tribes, which is crucial for firms to properly design their marketing strategy, and for scholars to extend prior marketing research.

It is rotating leaders who build the swarm: social network determinants of growth for healthcare virtual communities of practice

Purpose: The purpose of this paper is to identify the factors influencing the growth of healthcare virtual communities of practice (VCoPs) through a seven-year longitudinal study conducted using metrics from social-network and semantic analysis. By studying online communication along the three dimensions of social interactions (connectivity, interactivity and language use), the authors aim to provide VCoP managers with valuable insights to improve the success of their communities. Design/methodology/approach: Communications over a period of seven years (April 2008 to April 2015) and between 14,000 members of 16 different healthcare VCoPs coexisting on the same web platform were analysed. Multilevel regression models were used to reveal the main determinants of community growth over time. Independent variables were derived from social network and semantic analysis measures. Findings: Results show that structural and content-based variables predict the growth of the community. Progressively, more people will join a community if its structure is more centralised, leaders are more dynamic (they rotate more) and the language used in the posts is less complex. Research limitations/implications: The available data set included one Web platform and a limited number of control variables. To consolidate the findings of the present study, the experiment should be replicated on other healthcare VCoPs. Originality/value: The study provides useful recommendations for setting up and nurturing the growth of professional communities, considering, at the same time, the interaction patterns among the community members, the dynamic evolution of these interactions and the use of language. New analytical tools are presented, together with the use of innovative interaction metrics, that can significantly influence community growth, such as rotating leadership.

Editorial introduction: The power of words and networks

According to Freud "words were originally magic and to this day words have retained much of their ancient magical power". By words, behaviors are transformed and problems are solved. The way we use words reveals our intentions, goals and values. Novel tools for text analysis help understand the magical power of words. This power is multiplied, if it is combined with the study of social networks, i.e. with the analysis of relationships among social units. This special issue of the International Journal of Information Management, entitled "Combining Social Network Analysis and Text Mining: from Theory to Practice", includes heterogeneous and innovative research at the nexus of text mining and social network analysis. It aims to enrich work at the intersection of these fields, which still lags behind in theoretical, empirical, and methodological foundations. The nine articles accepted for inclusion in this special issue all present methods and tools that have business applications. They are summarized in this editorial introduction.

The impact of virtual mirroring on customer satisfaction

We investigate the impact of a novel method called "virtual mirroring" to promote employee self-reflection and impact customer satisfaction. The method is based on measuring communication patterns, through social network and semantic analysis, and mirroring them back to the individual. Our goal is to demonstrate that self-reflection can trigger a change in communication behaviors, which lead to increased customer satisfaction. We illustrate and test our approach analyzing e-mails of a large global services company by comparing changes in customer satisfaction associated with team leaders exposed to virtual mirroring (the experimental group). We find an increase in customer satisfaction in the experimental group and a decrease in the control group (team leaders not involved in the virtual mirroring process). With regard to the individual communication indicators, we find that customer satisfaction is higher when employees are more responsive, use a simpler language, are embedded in less centralized communication networks, and show more stable leadership patterns.