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Describes and discusses a series of researches specifically designed for analysis by sequential techniques — these were aimed at investigating the relationship between price, and customer preference, for a consumer durable article. Defines sequential analysis as a technique concerned with a cumulative simple analysis of results as they are obtained. Documents that investigation of the technique found that, for some market research applications, it has advantages over the conventional technique of completion of field research, followed by full analysis of the data obtained. Uses a sequential analysis chart to add weight to this technique, and discusses results to two test market product candidates (X and Y). Follows up this research by stating sequential analysis is a simple, yet elegant, technique which appears to open new possibilities to market research personnel in many areas. Concludes that sequential analysis has been proved to offer a simple, reliable pricing framework in a situation of dichotomous choice.

This study aims to explore the influence of creative tourist experiences (CTE) on tourists’ recommendation intentions (RCI) toward creative tourist destinations. This study examines the roles of tourist engagement and satisfaction in this relationship, proposing a sequential mediation model based on the cognitive-affective-conative model.

The research surveyed travelers to Kinnaur, Himachal Pradesh, India, using a structured questionnaire. Through purposive sampling data were collected from 413 generation Z (Gen Z in short) tourists. The study used exploratory factor analysis, confirmatory factor analysis and sequential mediation analysis. The present research used Model 6 by Andrew Hayes in the SPSS process macro to test the serial mediation.

The findings emphasize the importance of active engagement in creative tourism and its potential to transform cultural heritage into enriching experiences, thereby influencing tourists’ recommendation behaviors. Results of sequential mediation analysis show that there is a significant and positive impact of CTE on tourist’s RCI. Further, results showed the sequential mediation effect of tourist engagement and satisfaction on the relationship between CTE and RCI.

The findings offer valuable insights for destination managers and policymakers in creative tourism. Enhancing tourist engagement and satisfaction through creative experiences can effectively increase RCI, contributing to the sustainable management of cultural resources and preventing the over-commercialization of cultural heritage.

This research contributes to the literature on creative tourism by empirically testing the sequential mediation model and highlighting the pivotal role of tourist engagement and satisfaction in transforming creative experiences into positive behavioral outcomes. This study provides a nuanced understanding of the factors influencing tourists’ RCI in creative tourism contexts.

In order to deepen understanding of team processes in dynamic organizational contexts, we suggest that analyses employing techniques to identify and analyze team member interaction patterns and trajectories are necessary. After presenting a brief review of interaction data coding and reliability requirements, we first review examples of two approaches used in the identification and analysis of interaction patterns in teams: lag sequential analysis and T-pattern analysis. We then describe and discuss three statistical techniques used to analyze team interaction trajectories: random coefficient modeling, latent growth modeling, and discontinuous growth analysis. We close by suggesting several ways in which these techniques could be applied to data analysis in order to expand our knowledge of team interaction, processes, and outcomes in complex and dynamic settings.

The purpose of this paper is to examine the effect of gamification on students’ e-learning adoption. In addition, this paper examines the effect of two mediations, that is, flow and engagement between gamification and e-learning adoption by using sequential mediation analysis.

The authors used the online survey method to collect the 570 responses through convenience sampling procedure. Sequential mediation analysis technique was used to test the mediation hypothesis.

The findings of this paper revealed that gamification elements are an important feature of flow, engagement in e-learning adoption process. Also, the paper found that engagement in the learning process is a key element for students to adopt e-learning.

This paper makes its contribution to the literature related to gamification and e-learning adoption. The paper signifies the importance of gamification as an educational application in e-learning environment and its contribution in designing an interactive learning environment.

Empirically, to the best of the authors’ knowledge, it is the first paper to examine the sequential mediation model of gamification in the education sector in a developing nation like India. Furthermore, this paper also extends engagement and flow theory related to e-learning process by showing how students’ engagement and flow impact the e-learning adoption in the gamified environment.

The purpose of this study is to enable performing reliability-based design optimisation (RBDO) for a composite component while accounting for several multi-scale uncertainties using a large representative volume element (LRVE). This is achieved using an efficient finite element analysis (FEA)-based multi-scale reliability framework and sequential optimisation strategy.

An efficient FEA-based multi-scale reliability framework used in this study is extended and combined with a proposed sequential optimisation strategy to produce an efficient, flexible and accurate RBDO framework for fibre-reinforced composite laminate components. The proposed RBDO strategy is demonstrated by finding the optimum design solution for a composite component under the effect of multi-scale uncertainties while meeting a specific stiffness reliability requirement. Performing this using the double-loop approach is computationally expensive because of the number of uncertainties and function evaluations required to assess the reliability. Thus, a sequential optimisation concept is proposed, which starts by finding a deterministic optimum solution, then assesses the reliability and shifts the constraint limit to a safer region. This is repeated until the desired level of reliability is reached. This is followed by a final probabilistic optimisation to reduce the mass further and meet the desired level of stiffness reliability. In addition, the proposed framework uses several surrogate models to replace expensive FE function evaluations during optimisation and reliability analysis. The numerical example is also used to investigate the effect of using different sizes of LRVEs, compared with a single RVE. In future work, other problem-dependent surrogates such as Kriging will be used to allow predicting lower probability of failures with high accuracy.

The integration of the developed multi-scale reliability framework with the sequential RBDO optimisation strategy is proven computationally feasible, and it is shown that the use of LRVEs leads to less conservative designs compared with the use of single RVE, i.e. up to 3.5% weight reduction in the case of the 1 × 1 RVE optimised component. This is because the LRVE provides a representation of the spatial variability of uncertainties in a composite material while capturing a wider range of uncertainties at each iteration.

Fibre-reinforced composite laminate components designed using reliability and optimisation have been investigated before. Still, they have not previously been combined in a comprehensive multi-scale RBDO. Therefore, this study combines the probabilistic framework with an optimisation strategy to perform multi-scale RBDO and demonstrates its feasibility and efficiency for an fibre reinforced polymer component design.

Post-earthquake fire (PEF) can lead to a rapid collapse of structures partially damaged by earthquake. As there is almost no established PEF provisions by codes and standards, PEF investigations are therefore needed for those buildings. The paper aims to discuss these issues.

A non-linear PEF analysis comprises three steps, which are the application of gravity loads, earthquake loads and then fire loads. As a fire generally initiates on one floor and then spreads to other floors, applying a sequential fire is more realistic than applying a concurrent fire on several floors. Hence, in this study, the fire is applied sequentially to the floors with a time delay.

The results indicate a substantial reduction in the resistance of the damaged frame when subjected to PEF. In addition, the results of applying the PEF sequentially is more realistic than the concurrent fire.

It was better to perform an experimental test to have a better understanding of the issue.

PEF can potentially result in a catastrophe in areas located in seismic regions. Thus, investigating the effect of PEF on previously damaged structures is of importance.

Drawing on the social cognitive model of career self-management (CSM model) and deep learning theory, the authors' study aims to investigate the effect of knowledge sharing on career adaptability and explore how and when this effect occurs. The authors proposed a moderated sequential-mediation model linking knowledge sharing, knowledge depth, self-efficacy and career adaptability, moderated by reflective thinking.

The authors used a field survey involving 611 employees working in different enterprises in China to test the authors' predictions. For supplementary validation, the authors conducted a scenario-based experiment with a distinct sample of 148 employees from Chinese enterprises. The authors used hierarchical regression analysis, ANOVA analysis and moderated sequential-mediation analysis to test the hypotheses.

The results indicated a positive effect of knowledge sharing on career adaptability, sequentially mediated through knowledge depth and self-efficacy. Additionally, reflective thinking strengthened the positive effect of knowledge sharing on knowledge depth and further moderated the sequential mediating effect.

Previous research has predominantly focused on the perspective that individuals act as “recipients” from the environment in developing career adaptability. Instead, the authors adopt a “giving” perspective by investigating the influence of knowledge sharing on career adaptability, which advances the existing knowledge on the predictors of career adaptability.

The recent high food price and volatility, as well as economic recession, have reversed the last decade's progress in reducing hunger and poverty. This aim of this paper is to conduct a factor and sequential typology analysis to identify groups of countries categorized according to five measures of food security.

The recent high food price and volatility, as well as economic recession, have reversed the last decade's progress in reducing hunger and poverty. This paper conducts a factor and sequential typology analysis to identify groups of countries categorized according to five measures of food security – consumption, production, imports, distribution, and agricultural potential – by using indicators from 175 countries. The analysis first identifies five distinct food security groups, measured by the levels of nutrient intake, and then further splits these groups based on indicators of food production, trade security, and agricultural potential.

The results suggest that the terms of “developing country” or “low income country” can be inaccurate in the discussion of food security because they are too general and can actually mask the extreme heterogeneity in different aspects of food security. The results also indicate that different responses are needed by different types of food‐insecure countries to address their unique food and economic challenges.

The typology of food security and linkage between agricultural potential and food security contribute to a better understanding of the effectiveness of different policy interventions under a country's unique conditions.

Purpose – This chapter examines disputes produced by two young children during computer game playing and considers how the disputes were related to the children's ongoing activity.

Methodology/approach – The study is framed by ethnomethodology and conversation analysis. Sequential analysis of recorded data details the mutual production of disputes during talk and interaction.

Findings – The analysis establishes how the children made each other accountable to the agreed-upon way of playing the game after one child offered to show the other how to play. Conflict developed during the game and disputes built upon previous disputes, especially in relation to claims made about knowing how to play.

Research implications – The disputes here are best understood in relation to how disagreement was avoided initially but then emerged as the gaming progressed. Examining disputes in the course of computer activity shows how the children turn agreement into disagreement over time.

Social implications – This study establishes some of the ways that disputes arise out of young children's social interactions during computer game playing and how disputes are related, or not, to shared understandings of what is going on moment by moment in the game.

Originality – Overall, this chapter provides a detailed sequential analysis across computer activity and establishes how the children's disputes challenge the order of game playing as the game progresses.

The purpose of this paper is to establish and implement a direct topological reanalysis algorithm for general successive structural modifications, based on the updating matrix triangular factorization (UMTF) method for non-topological modification proposed by Song et al. [Computers and Structures, 143(2014):60-72].

In this method, topological modifications are viewed as a union of symbolic and numerical change of structural matrices. The numerical part is dealt with UMTF by directly updating the matrix triangular factors. For symbolic change, an integral structure which consists of all potential nodes/elements is introduced to avoid side effects on the efficiency during successive modifications. Necessary pre- and post processing are also developed for memory-economic matrix manipulation.

The new reanalysis algorithm is applicable to successive general structural modifications for arbitrary modification amplitudes and locations. It explicitly updates the factor matrices of the modified structure and thus guarantees the accuracy as full direct analysis while greatly enhancing the efficiency.

Examples including evolutionary structural optimization and sequential construction analysis show the capability and efficiency of the algorithm.

This innovative paper makes direct topological reanalysis be applicable for successive structural modifications in many different areas.