Purpose: This study explores whether and how four main factors of short-branded video content (content matching, information relevance, storytelling and emotionality) facilitate consumer engagement (likes, comments and shares), as well as the moderating effect of the release time (morning, afternoon and evening) in such relationships.Design/methodology/approach: This study uses Python to write programs to crawl relevant data information, such as consumer engagement and short video release time. It combines coding methods to empirically analyze the impact of short-branded video content characteristics on consumer engagement. A total of 10,240 Weibo short videos (total duration: 238.645 h) from 122 well-known brands are utilized as research objects.Findings: Empirical results show that the content characteristics of short videos significantly affected consumer engagement. Furthermore, the release time of videos significantly moderated the relationship between the emotionality of short videos and consumer engagement. Content released in the morning enhanced the positive impact of warmth, excitement and joy on consumer engagement, compared to that released in the afternoon.Practical implications: The findings provide new insights for the dissemination of products and brand culture through short videos. The authors suggest that enterprises that use brand videos consider content matching, information relevance, storytelling and emotionality in their design.Originality/value: From a broader perspective, this study constructs a new method for comprehensively evaluating short-branded video content, based on four dimensions (content matching, information relevance, storytelling and emotionality) and explores the value of these dimensions for creating social media marketing success, such as via consumer engagement.

Purpose: The purpose of this paper is to answer “Why do Chinese consumers use IOT systems?” and “Do consumers’ cognitive and affect experiences moderate the relationship between psychological perception factors and perceived usefulness?” Design/methodology/approach: In-depth interview with consumers and experts had been conducted and then the perceived psychological factors that influence perceived usefulness had been summarized. Based on a survey test of 337 smart home users, this study applies partial least squares technique analysis to test the research model. Findings: The research results show that perceived psychological factors (perceived ease of use, perceived intelligence, perceived convenience and perceived privacy risk) have significant effect on the intention and behavior of IOT systems usage through perceived usefulness. Cognitive experience moderates the relationship between perceived ease of use and perceived usefulness, perceived privacy risk and perceived usefulness; affect experience moderates the relationship between perceived ease of use and perceived usefulness. Research limitations/implications: The current study mainly tested the antecedents of consumers’ usage of IOT systems, and the outcome of using the system was not investigated. Future research can examine the outcome (e.g. satisfaction, perceived value) by using the expectation-confirmation theory. Originality/value: This study provides a useful insight into the key driving factors in consumers’ intention and behavior of using IOT systems. The previous studies over IOT systems have not observed consumers’ perception of IOT systems, but in fact IOT systems are being applied to more and more personal users.

Purpose: Based on the cue utilization theory and congruity theory, the purpose of this paper is to investigate the mediating effects of perceived quality on the relationships between category characteristics and purchase intention for private labels. Design/methodology/approach: To examine the research hypotheses, the authors conducted a questionnaire survey on 703 adult consumers in China. Findings: The results show that perceived quality fully mediates the relationships between category complexity, risk importance, category quality variation, product signatureness and purchase intention. In addition, consumers’ knowledge moderates the relationship between perceived quality and purchase intention. The implications and future research directions are discussed in this study. Originality/value: The results show that the category complexity is positively related to consumers’ perceived quality. Although opposite to the conclusions in prior research, the findings are consistent with the unique phenomenon in China, that is, to label the name and location of the contract manufacturers. The authors investigate the moderating role of consumer knowledge, which will provide meaningful guidance for the Chinese retailing market.

In the resource levelling problem (RLP) under uncertainty, existing studies focus on obtaining an open-loop activity list that is not updated during project execution. In project management practice, it is also necessary to address more situations, such as activity overlaps and resource breakdowns. In this paper, we extend the uncertain RLP by proposing a resource levelling problem with multiple uncertainties (RLP-MU) that simultaneously considers uncertainties in activity durations, activity overlaps and resource availabilities. We formulate the RLP-MU as a Markov decision process model. Aimed at levelling resource usage by dynamically scheduling activities at each decision point based on the observed information, we develop a hybrid open–closed-loop approximate dynamic programming algorithm (HOC-ADP). In the HOC-ADP, we devise a closed-loop rollout policy to approximate the cost-to-go function and use the concept of the average project to avoid time-consuming simulation. A greedy-decoding-based estimation of distributed algorithm is also devised to construct an open-loop policy that is embedded in the HOC-ADP to further improve it. We additionally develop a simulation algorithm to evaluate the resource levelling performance of the HOC-ADP. Computational experiments on a benchmark dataset consisting of 540 problem instances are conducted to analyze the performance of the HOC-ADP, and the impact of various factors on resource levelling are investigated. The comparison experimental results indicate that our HOC-ADP outperforms the state-of-the-art meta-heuristics.