Purpose

This study aims to understand if an online dating app is considered an acceptable channel to conduct advertising activities and understand the differences between Generations X, Y and Z for such acceptance.

Design/methodology/approach

A total of 411 Tinder users’ reactions were obtained and analyzed using text mining to compute the sentiment score of each response, and a Kruskal–Wallis H test to verify if there are statistical differences between each generation.

Findings

The results showed positive acceptability toward the marketing campaign on Tinder, especially Z Generation. Nevertheless, the statistical analysis revealed that the differences between each generation are not statistically significant.

Research limitations/implications

The main limitation relates to the fact that the participants, during the data collection, revealed their identification, perhaps leading to acquiescence bias. In addition, the study mainly covered the male population. A balanced sample would be positive to examine any possible differences between gender.

Practical implications

Results provide an essential indication for companies regarding their marketing activities conducted on Tinder to fully exploit the possibility of using Tinder as an alternative and valuable channel to conduct marketing activities.

Originality/value

Up until now, no studies tried to understand the effect of a marketing activity online on an online dating app.

This paper presents a novel analysis of two feed-in tariffs (FIT) under market and regulatory uncertainty, namely a sliding premium with cap and floor and a minimum price guarantee. Regulatory uncertainty is modeled with a Poisson process, whereby a jump event may reduce the tariff before the signature of the contract. Using a semi-analytical real options framework, we derive the project value, the optimal investment threshold, and the value of the investment opportunity for these schemes. Taking into consideration the optimal investment threshold, we also compare the two aforementioned FITs with the fixed-price FIT and the fixed-premium FIT, which are policy schemes that have been extensively studied in the literature. Our results show that increasing the likelihood of a jump event lowers the investment threshold for all the schemes; moreover, the investment threshold also decreases when the tariff reduction increases. We also compare the four schemes in terms of the corresponding optimal investment thresholds. For example, we find that the investment threshold of the sliding premium is lower than the minimum price guarantee. This result suggests that the first regime is a better policy than the latter because it accelerates the investment while avoiding excessive earnings for producers or excessive payments for consumers.

Absenteeism affects state-owned companies who are obliged to undertake strategies to prevent it, be efficient and conduct effective human resource (HR) management. This paper aims to understand the reasons for Public Administration Employees’ (PAE) absenteeism and predict future employee absences. Data from 17,600 PAE from seven public databases regarding their 2016 absences was collected, and the Recency, Frequency and Monetary (RFM) and Support Vector Machine (SVM) algorithm was used for modelling the absence duration, backed up with a 10-fold cross-validation scheme. Results revealed that the worker profile is less relevant than the absence characteristics. The most concerning employee profile was uncovered, and a set of scenarios is provided regarding the expected days of absence in the future for each scenario. The veracity of the absence motives could not be proven and thus are totally reliable. In addition, the number of records of one absence day was disproportionate to the other records. The findings are of value to the Human Capital Management department in order to support their decisions regarding the allocation of workers and productivity management and use these valuable insights in the recruitment process. Until now, little has been known concerning the characteristics that affect PAE absenteeism, therefore enriching the necessity for further understanding of this matter in this particular.

• Purpose – Strategic goal achievement in every sector of a company relies fundamentally on the firm’s employees. This study aims to disclose the factors that spur employees of major Information Technology (IT) companies in the United States (US).
• Design/methodology/approach – In this paper, 15,000 reviews from the top 15 United States IT companies were collected from the social media platform Glassdoor to uncover the factors that satisfy IT employees. To learn the most meaningful features that influence the scores, positive and negative remarks, as well as advice to the management team, were analyzed through a support vector machine.
• Findings – Results highlight a positive attitude of coworkers, contributing to a positive environment and job satisfaction. However, unsatisfied IT employees reveal that work exhaustion is the main reason for their job dissatisfaction.
• Practical implications – IT human resource departments can use these valuable insights to align their strategies in accordance with their employees’ desires and expectations in order to thrive.
• Originality/value – The study highlights the relevance of IT companies to understand the reasons behind their employees’ satisfaction. Up until now, little is known concerning the variants of job satisfaction among IT employees, enriching the understanding in this particular professional area.

Building on the numerical solution by Ribeiro et al. (2108), this paper proposes a model to assess the impact of volume uncertainty on construction projects’ value and on the optimal bidding price. The model’s outcome is the threshold amount for the incremental investment that managers have to undertake in order to resolve the uncertainty regarding the volume of work to be performed. Any amount of investment below the threshold will add value to the project and produces a more competitive bid price. A numerical example is presented, and a sensitivity analysis is performed to the model’s most relevant components.