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Marketing professionals are under pressure to implement methods and metrics that demonstrate the value of the function. This paper aims to propose a model to measure marketing performance, focusing on four categories of metrics and two types of factors that influence the effectiveness of the assessment process.

The paper is organized in three parts. The first part includes a synthesis of the theoretical background on the subject. Next, the rationale and architecture of the model are presented, together with an explanation of the elements that compose it. A reflection on the work developed is presented in the last section.

Benefits regarding how to best assess marketing practice are considerable, as organizations with effective performance measurement systems tend to show better results than others. In this context, the choice of metrics is important, but it is also necessary to understand the mechanisms through which the effectiveness of the measurement process can be improved.

Literature has mainly focused attention on the effect of individual programs on specific measures or on conceptual models that do not sufficiently address all major elements in the marketing assessment process. This work extends previous contributions on the subject, presenting a model that combines metrics with factors underlying the measurement process.

The purpose of this study is to revisit brand performance metrics (BPMs) (brand affinity, brand content and knowledge, brand image, brand ethics and brand value) and evaluate the moderated mediation effect of relationship quality (mediator) and relationship duration (moderator) in brand performance and customer loyalty relationship in an Indian banking context.

The research model was tested in the Indian banking sector. The primary data was collected from the 1,000 account holders of five Indian public and private banks. The data was analysed and validated using exploratory factor analysis and confirmatory factor analysis. Structural equation modelling and the Hayes process were used for testing the hypotheses.

The study results established BPMs as a four-dimensional structure comprising brand affinity, brand content and knowledge, brand image, brand ethics and brand value. The BPMs significantly positively impact relational quality (RQ) and customer loyalty. Further results also prove the existence of moderated mediation effect on BPMs and customer loyalty link and portray that the impact of BPMs on customer loyalty is mediated by the RQ and influenced by relationship duration.

The study is confined to the Indian banking sector. It did not examine the dimension-wise impact of brand performance indicators on RQ and customer loyalty. Future research is required to explore their influence in banking and other sectors.

The study findings suggest that to enhance brand performance, banks need to follow excellence in every conduct, take immediate actions against inappropriate behaviour, consistently update their relevant and valuable contents (news, videos, white papers, e-books, case studies, FAQ’s, photos, etc.) on their websites and also introduce loyalty schemes to reimburse customers’ interests with some substantial benefits such as rebates, discounts, annual gifts and extraordinary or additional services. These strategies can pave the way for enhancing long-term quality relationships between customers and their service providers and increasing customer loyalty.

To the best of the authors’ knowledge, the study is a maiden attempt to assess the effect of BPMs on customer loyalty in the presence of RQ and at the value of relationship duration/length. Besides, the study results also prove the existence of moderated mediation effect and portray that the impact of customer equity and relational benefits on customer loyalty is influenced by relationship duration and mediated by RQ.

The purpose of this paper is to examine the impact of affiliate marketing strategies as a tool for increasing customers' engagement and vulnerability over financial services. This is attempted by examining the connection between affiliate marketing factors and customers' brand engagement and vulnerability metrics.

The authors developed a three-staged methodological context, based on the 7 most known centralized payment network (CPN) firms' website analytical data, which begins with linear regression analysis, followed by hybrid modeling (agent-based and dynamic models), so as to simulate brand engagement and vulnerability factors' variation in a 180-day period. The deployed context ends by applying the cognitive modeling method of producing heatmaps and facial analysis of CPN websites to the selected 47 vulnerable website customers, for gathering more insights into their brand engagement.

Throughout the simulation results of the study, it becomes clear that a higher number of backlinks and referral domains tend to increase CPN firms' brand-engaged and vulnerable customers.

From the simulation modeling process, the implication for backlinks and referral domains as factors that enhance website customers' brand engagement and vulnerability has been highlighted. A higher number of brand-engaged website customers could mean that vulnerable categories of customers would be impacted by CPNs' affiliate marketing. Improving those customers' knowledge of the financial services utility is of utmost importance.

The outcomes of the research indicate that online banking service providers can increase their customers' engagement with their brands by adopting affiliate marketing techniques. To avoid the increase in customers' vulnerability, marketers should aim to apply affiliate marketing strategies to domains relevant to the provided financial services.

The paper's outcomes provide a new approach to the literature, where the website customer's brand engagement comes out as a valuable metric for estimating online banking sector customers' vulnerability.

The metaverse, which is now revolutionizing how brands strategize their business needs, necessitates understanding individual opinions. Sentiment analysis deciphers emotions and uncovers a deeper understanding of user opinions and trends within this digital realm. Further, sentiments signify the underlying factor that triggers one’s intent to use technology like the metaverse. Positive sentiments often correlate with positive user experiences, while negative sentiments may signify issues or frustrations. Brands may consider these sentiments and implement them on their metaverse platforms for a seamless user experience.

The current study adopts machine learning sentiment analysis techniques using Support Vector Machine, Doc2Vec, RNN, and CNN to explore the sentiment of individuals toward metaverse in a user-generated context. The topics were discovered using the topic modeling method, and sentiment analysis was performed subsequently.

The results revealed that the users had a positive notion about the experience and orientation of the metaverse while having a negative attitude towards the economy, data, and cyber security. The accuracy of each model has been analyzed, and it has been concluded that CNN provides better accuracy on an average of 89% compared to the other models.

Analyzing sentiment can reveal how the general public perceives the metaverse. Positive sentiment may suggest enthusiasm and readiness for adoption, while negative sentiment might indicate skepticism or concerns. Given the positive user notions about the metaverse’s experience and orientation, developers should continue to focus on creating innovative and immersive virtual environments. At the same time, users' concerns about data, cybersecurity and the economy are critical. The negative attitude toward the metaverse’s economy suggests a need for innovation in economic models within the metaverse. Also, developers and platform operators should prioritize robust data security measures. Implementing strong encryption and two-factor authentication and educating users about cybersecurity best practices can address these concerns and enhance user trust.

In terms of societal dynamics, the metaverse could revolutionize communication and relationships by altering traditional notions of proximity and the presence of its users. Further, virtual economies might emerge, with virtual assets having real-world value, presenting both opportunities and challenges for industries and regulators.

The current study contributes to research as it is the first of its kind to explore the sentiments of individuals toward the metaverse using deep learning techniques and evaluate the accuracy of these models.

Academics and businesses alike have begun to recognise sustainability as a vital component of supply chain competitive advantage in recent years. Inconclusive results have been found in empirical studies of sustainable supply chain management (SSCM) that have ignored contextual variables concerning the dynamic role of firm capability in favour of testing alternative assumptions about the effect of various elements of the triple bottom line (TBL) on firm performance outcomes. The present study examines whether and how firm capabilities mediate the connection between SSCM, from a TBL standpoint, and firm financial performance outcomes.

Using the stakeholder theory, the study employed 325 survey responses from firms operating in different industries in Ghana (a less-researched context but one that plays a key role regarding SSCM practices) and the partial least squares structural equation model (PLS-SEM) technique to simultaneously assess the relationships amongst the variables.

It was discovered that the connections between all the TBL facets of SSCM practices and firm performance are positive and significant, and these relationships are mediated by firm capabilities.

By examining the underlying variables and relationships that contribute to the establishment of the rather complex relationship between SSCM practices from a TBL perspective and the performance of a firm, the research contributes to current knowledge on SSCM practices, firm capabilities and firm performance.

The paper provides a step-by-step guide in the guise of a roadmap for service improvement initiatives using importance performance map analysis (IPMA).

To empirically illustrate how IPMA can be applied to any service industry, three sectors are considered; sports and fitness (study A), hospitality (study B) and higher education (study C). Following the proper selection of measuring instruments and their evaluation using structural equation modeling-partial least squares (Smart-PLS), IPMA is applied to identify those attributes having strong total effects (high importance) over the targeted construct (satisfaction) but which also have low average latent variable scores (low performance).

For sports and fitness (study A), the physical aspects and programme quality require managerial attention. For the hospitability sector (study B), it is service commitment, interaction quality and internal sense of happiness. Whereas for higher education (study C), it is administrative quality as well as the element of transformative quality, namely the university’s role in adding to its students’ emotional stability, which needs the attention of the top management.

This study provides researchers and practitioners with a roadmap for applying PLS-SEM and IPMA for continuous service quality improvement. The roadmap extends upon Ringle and Sarstedt’s (2016) work. It highlights critical decisions that need to be considered in the pre-analytical stages of the IPMA application, i.e. at the research design phase in selecting the most appropriate service quality measurement model specifications. It not only contributes to the existing body of knowledge by providing empirical evidence to advance theory development in the quality management field but also has implications for the practitioners in any service sector on where to focus their attention for an effective service improvement.

The implementation of control systems allows marketing managers to improve operational decisions and organizational results. This paper aims to identify the relationship between control combinations and organizational results and analyze the relationships between the variables attributed to the marketing managers and with marketing control combinations. Decisions involving marketing control combine formal and informal mechanisms and generate control systems that have a favorable relationship with organizational results.

The paper is based on 301 cross-sectional surveys among marketing managers. The classification procedure based on metric distance was implemented to identify the marketing control combinations. A hierarchical cluster analysis was carried out with perceptions about formal and informal control, to validate the control combination classifications. Finally, a discriminant analysis and ANOVA test were carried out for exploring factors associated with the managers. The data analysis was supported by IBM SPSS Statistics 24 software.

The authors found evidence that, when managers perceive high-control systems, the perception of non-financial and financial results is always better, but the presence of high-clan control also returns optimal results. In addition, the manager's satisfaction levels and work motivation are higher with high control systems than with other control systems.

This study contributes to the existing knowledge by providing a broader empirical basis to extend conceptual frameworks about marketing control combinations that emerge in practice.

企業設置營銷控制系統來進行營銷控制,這可讓市場經理能改善其營運決策和組織成果。本文擬確定控制合併與組織成果的關係;本文亦擬分析涉及市場經理的變數與營銷控制合併的關係。涉及營銷控制的決策會結合正式和非正式的機制,而這些決策會帶來與組織成果有良性關係的控制系統。

本研究乃基於對市場經理進行的301項橫斷調查。研究人員實施基於度量距離的分類程式,來確定營銷控制合併;為了證實有關的控制合併分類是正確的,研究人員就對正式控制和非正式控制的觀感和看法、進行了階層式分群法分析;最後,研究人員進行了判別分析和變異數分析 (ANOVA), 以探索與經理有關聯的因素。有關的數據分析得到IBM公司的SPSS (統計產品與服務解決方案) Statistics 24 (統計軟體) 的支持。

我們證實了、若主管感知高控制的系統,其對非財務結果和財務結果的看法必會較好的,但高社群控制亦會帶來最佳的結果。我們亦證實了高控制系統,較其它控制系統,更能提高主管的滿意程度和工作動機。

本研究提供了一個更廣闊的經驗基礎,以擴展涉及在實踐中出現的營銷控制合併的概念框架,就此,本研究豐富了這方面的知識。

The paper’s main goal is to examine the relationship between the video marketing of financial technologies (Fintechs) and their vulnerable website customers’ brand engagement in the ongoing coronavirus disease 2019 (COVID-19) crisis.

To extract the required outcomes, the authors gathered data from the five biggest Fintech websites and YouTube channels, performed multiple linear regression models and developed a hybrid (agent-based and dynamic) model to assess the performance connection between their video marketing analytics and vulnerable website customers’ brand engagement.

It has been found that video marketing analytics of Fintechs’ YouTube channels are a decisive factor in impacting their vulnerable website customers’ brand engagement and awareness.

By enhancing video marketing analytics of their YouTube channels, Fintechs can achieve greater levels of vulnerable website customers’ engagement and awareness. Higher levels of vulnerable customers’ brand engagement and awareness tend to decrease their vulnerability by enhancing their financial knowledge and confidence.

Fintechs should aim to increase the number of total videos on their YouTube channels and provide videos that promote their customers’ knowledge of their services to increase their brand engagement and awareness, thus reducing their vulnerability. Moreover, Fintechs should be aware not to over-post videos because they will be in an unfavorable position against their competitors.

This research offers valuable insights regarding the importance of video marketing strategies for Fintechs in promoting their vulnerable website customers’ brand awareness during crisis periods.

This study analyzes the impact of sports social media on a country regarding three international events connected to the brand Spain. It examines (1) the use and importance of various social media platforms in sports events and (2) identifies the countries generating the most social media content.

A total of 1,711,084 posts were collected for analysis, focusing on FIFA World Cup Qatar 2022, XLI Marathon Valencia Trinidad Alfonso 2022 and Davis Cup 2022, with a particular emphasis on the Spain brand. Through Atribus, diverse social media data were recovered and analyzed. Later, we recommended employing various metrics and ANOVAs to address the research questions. Additionally, we conducted a sentiment analysis.

The results show differences between (1) the use and relevance of social network platforms and events and (2) the content generated by different countries. The practical implications offer valuable insights for sports event organizers, destination managers and other stakeholders. The research implications suggest potential avenues for future research based on the observed patterns and behaviors in social media posts related to sports events and Brand Spain.

(1) Some papers have studied the role of sports events’ social media, ignoring the comparison among different social media platforms; (2) usually, previous literature has focused on a single event or sport and (3) although there is considerable research related to the strategic and operational Inés Küster Boluda Inés Küster Boluda role of social media, there is less systematic analysis related to the extent sports events use social media in general and in specific social media platforms and virtually nonexistent studies that employ index measurements.

本研究擬分析就三個與西班牙品牌有關的國際體育賽事而言，體育社交媒體對一個國家的影響。俱體而言，本研究擬探討： (一) 、各體育賽事社交媒體平台的使用和其重要性，以及 (二) 、是哪些國家生成最多的社交媒體內容。

研究人員收集共計1,711,084帖子以便進行分析;其焦點放在2022年卡塔爾世界盃 (即2022年國際足聯世界盃) ，2022年特尼利尼達阿方索馬拉松賽－瓦倫西亞 (XLI Marathon Valencia Trinidad Alfonso 2022) 和2022年台維斯盃;研究人員特別把重點放在西班牙品牌上。研究人員透過 Atribus 重新取得多種多樣的社交媒體數據，然後進行分析。之後，研究人員建議使用不同的度量和方差分析去處理各研究問題，以及進行了情感分析。

研究結果顯示了以下兩者之差異：(一) 、社交網絡平台和比賽項目的使用和關聯，以及 (二) 、不同國家生成的內容。從這個研究發現，體育賽事的籌辦者、目的地管理人員和其它利益相關者，均會獲得寶貴的實務啟示;至於就未來學術研究的路向而言，學者和研究人員或許可觀察關於體育賽事和西班牙品牌的社交媒體帖子裡顯示的模式和行為，從而找到合適的研究路徑。

本研究有以下的貢獻：(一) 、從前的研究多只探討關於體育賽事的社交媒體所扮演的角色，而忽略了要比較不同社交媒體平台的需要;(二) 、過去的文獻通常聚焦於單一的賽事或運動上;以及 (三) 、雖然探討關於社交媒體在戰略上和在操作上所扮演的角色的研究為數不少，但甚少研究、就體育賽事大體使用社交媒體的程度，或使用特定的社交媒體平台的程度進行分析和探討。再者，幾乎沒有學者或研究人員在有關的研究上使用指標測量法;就此三點而言，本研究可說填補了有關的研究空白。

The United Nations member countries adopted a set of 17 sustainable development goals (SDGs) to achieve a better and more sustainable future for all. It encourages the use of sustainable practices during new product development (NPD). Competitiveness has put pressure on organizations to maintain their market share and look for new approaches related to NPD. The current study aims to focus on creating a framework that can help to achieve the SDGs by adopting agile new product development (ANPD) practices and Industry 4.0 technologies.

From the literature, various ANPD practices, Industry 4.0 technologies, performance metrics, their interconnection and their contribution toward achieving SDGs are extracted. The weights of selected Industry 4.0–ANPD practices are computed by robust best worst method (RBWM), and the Fuzzy-VIKOR method is used to rank the selected performance metrics. To test the robustness of the developed framework, sensitivity analysis is also performed.

The results show that among the various Industry 4.0–ANPD practices “Multi-skilled employees” have the highest weight followed by “Customer requirement analysis and prioritization.” Whereas for performance metrics, “The number of innovative products launched per year” is ranked first, with the “Average time between two launches” at second place.

This research contributes to the adoption of ANPD practices and Industry 4.0 technologies for the achievement of the business SDGs. The shortlisted Industry 4.0–ANPD practices will help in resolving the social and environmental issues. The set of performance metrics will help practitioners and managers to evaluate the performance of ANPD in the context of business SDGs.

This study adds to the understanding related to Industry 4.0–ANPD practices adoption. And to the best of the authors’ knowledge, it is believed that no similar work has been done previously and by using industry insights into technology components, this work contributes to valuable insights into the subject.