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Utilization of industrial and agricultural waste products as cement replacement materials in concrete technology has been an interesting subject of research for economical, environmental, and technical reasons. Portland cement incorporating these cement replacement materials improves corrosion resistance of carbon steel. Sugar cane bagasse is considered as waste in sugar mills and dumped in open space or used as fuel for boilers. The main purpose of the study is to investigate corrosion performance of reinforcing carbon steel in bagasse ash (BA) blended cement concrete and compare it with control concrete.

BA is prepared by burning boiler‐fired ash at a controlled temperature of 650°C for 1 h and cooled. The ash is then ground to a fineness of 46 μm as Pozzolanic material and blended in concrete in various cement replacement levels. The corrosion behaviour of carbon steel in BA blended concretes exposed to alternate dry‐wet cycles in 3.0 percent NaCl solution for 18 months was studied using gravimetric weight loss, linear polarization, and electrochemical impedance measurement techniques. The resistance to chloride ion penetration of BA blended concretes after 28 and 90 days and compressive strength of BA blended concrete cubes after 7, 14, 28, and 90 days curing also was evaluated.

The experimental results indicated that the corrosion rate of reinforcing steel and chloride penetration were significantly reduced, and compressive strength was increased, with the incorporation of BA up to 20 percent replacement in concrete. It was observed also that a relatively good correlation between linear polarization and impedance measurements with respect to corrosion current values on the reinforcing steel within BA blended concretes.

BA may be considered as a better substitute than other mineral admixtures for durable concrete structures. The study fulfilled the objective of the investigation and contributes to research on corrosion protection of carbon steel in concrete.

This study aims to extend research in marketing on two important relational constructs, customer satisfaction and brand attachment, by comparing their long-term effects on customer behaviors with different levels of performance difficulty in a relatively understudied domain of durable products.

Using a two-stage quantitative study with US customers from five durable product categories, the authors first explored the hierarchy of customers’ loyalty behaviors based on increasing effort in a pretest study (N = 675). Then, the authors tested the effectiveness of satisfaction and brand attachment for customers’ loyalty behaviors over a nine-month period in a longitudinal study (N = 2,284) with customers from the same product categories.

Compared to satisfaction, brand attachment emerges as a stronger long-term predictor of customer behaviors. The performance difficulty of customer behaviors positively moderates the impact of brand attachment and negatively moderates the impact of customer satisfaction. Brand attachment is particularly effective in predicting difficult-to-perform customer behaviors, which require customers to expend resources such as time and money. Customer satisfaction is mainly effective for predicting easy-to-perform behaviors, but its long-term impact is significantly lower for easy-to-perform behaviors than brand attachment.

The use of consumer durables in the study and samples from only one country restricts the generalizability of the findings.

The complementary roles of customer satisfaction and brand attachment are highlighted. Only satisfying customers is not enough to engage customers in behaviors that require resources such as money, time and energy for the brand.

A comparative study on the long-term effectiveness of two established relational metrics in explaining different customer behaviors varying in their performance difficulty in an understudied domain of durable products.

This study focuses on Aaker's Brand Equity Model, to check the effect of brand equity determinants on booking intention (BI) for ridesharing in India. The study also explores the moderation of ecologically conscious consumer behavior (ECCB) on the multiplicative effect of brand awareness (BAw), brand association (BA) and perceived quality (PQ) in influencing the BI.

Responses from 393 Indian ridesharing users were collected using judgmental sampling and were analyzed using Hayes Process macro.

The study found a direct relationship between BAw and BI, BAw and BA, BAw and PQ, BA and PQ, PQ and BI, and BA and BI. Findings revealed mediation of BA in BAw and BI relationship and PQ in BAw and BI relationship. Results revealed that BA and PQ serially mediate BAw and BI relationship. ECCB moderates PQ and BI relationship but not BAw and BI relationship.

Serial mediation and moderated-mediation results draw various theoretical implications for determinants of Aaker's Brand Equity model and ECCB.

The research has several implications for managers in view of brand equity determinants and ECCB. The study also contributes to policy implications.

Study's novel contributions are mediation, serial mediation between brand equity determinants, and moderation of ECCB between BAw and BI for ridesharing.

This study aims to analyze the contribution of business angels (BAs), defined as wealthy individuals who provide risk capital to entrepreneurial firms without family connections, in Estonia, an emerging country in Eastern Europe.

This study compared the data of the financial and non-financial performance of BA-backed firms with that of “twin” non-BA-backed firms, extracted from all Estonian unlisted firms using propensity score matching.

The results of the comparative analysis showed that BAs were patient enough to allow their investees to spend for future growth rather than squeezing profit from increased sales. This is not patience without options for a BA in a situation in which the investee's sales are deteriorating, but rather deliberate patience in the presence of options for a BA where the investee's sales growth is increasing, contrary to conventional investor behavioral principles. It also showed that BAs' post-investment involvement did not make a direct contribution to their investees' sales, although BAs contributed to the sales increase through BA funding itself.

This study has two unique research contributions. First, it shows that the patience of BAs was not a by-product but was intentional, and adds to the debate on whether BAs are patient investors. Second, there are only a few studies on the contribution of BAs to their investees in emerging countries; this study aims to help fill this research gap using the case of Estonia.

The purpose of this paper is to empirically analyze how brand authenticity (BA) as perceived by consumers who take health functional foods (HFF) strengthen the brand relationship quality (BRQ) and positively affects brand loyalty.

The five sub-dimensions of BA perceived by HFF consumers, elicited through a focus group interview, were conceptualized as a second-order reflective construct. To identify the influences of the sub-dimensions of BA on each construct of the BRQ and the influence on brand loyalty though mediating BRQ, an empirical analysis was done using partial least squares-based structural equation modeling.

All the sub-dimensions of BA positively affect each of the BRQ s (brand satisfaction, brand trust and brand commitment) excepting product authenticity on brand commitment, and originality on brand trust. The impact of BA positively affects brand loyalty by mediating brand relationship qualities.

It is found that BA is an important antecedent for forming BRQ with consumers in the HFF industry, in which building trust with consumers is important. BA is an important factor in brand management of HFF.

In the digital age, the use of data and analytical capabilities to guide business decisions and operations plays a strategic role for organizations to gain competitive advantage (CA). However, the paths by which analytical capabilities convey their effect to CA are not yet fully known and few studies address the role of behavioral and cultural aspects of related of analytical capabilities. The purpose of this paper is to analyze how data-driven culture (DDC) and business analytics (BA) affect CA, considering the mediating effects of big data visualization (BDV) and organizational agility (OA).

A survey was conducted with 173 managers who are BDV and BA users in Brazilian organizations of various economic segments. The data were analyzed through structural equation modeling and mediation tests.

The evidence indicates that DDC and BDV are antecedents of BA. The following complementary mediations were discovered: BDV in the relationship between DDC and BA; BA in the relationship between DDC and CA; and OA in the relationship between BA and CA. It was also discovered that OA explains the transmission of most of the effect of BA to CA.

This study can help organizations to understand the importance of cultural and behavioral aspects related to the use of the analytical capabilities. Thereby, managers can establish policies and strategies to extract value from data and leverage business agility and competitiveness through use BDV and BA.

This study fills an important research gap by developing an original research model and discussing empirical evidence on how DDC and BA affect CA, considering the mediating effects of BDV and OA.

The purpose of this paper is to explore the role of storytelling in data interpretation, decision-making and individual-level adoption of business analytics (BA).

Existing theory is extended by introducing the concept of BA data-driven storytelling and by synthesizing insights from BA, storytelling, behavioral research, linguistics, psychology and neuroscience. Using theory-building methodology, a model with propositions is introduced to demonstrate the relationship between storytelling, data interpretation quality, decision-making quality, intention to use BA and actual BA use.

BA data-driven storytelling is a narrative sensemaking heuristic positively influencing human behavior towards BA use. Organizations deliberately disseminating BA data-driven stories can improve the quality of individual data interpretation and decision-making, resulting in increased individual utilization of BA on a daily basis.

To acquire a deeper understanding of BA data-driven storytelling in behavioral operational research (BOR), future studies should test the theoretical model of this study and focus on exploring the complexity and diversity in individual attitudes toward BA.

This study provides practical guidance for business practitioners who struggle with interpreting vast amounts of complex data, making data-driven decisions and incorporating BA into daily operations.

This cross-disciplinary study develops existing BOR, storytelling and BA literature by showing how a novel BA data-driven storytelling approach can facilitate BA adoption in organizations.

Gives an in depth view of the strategies pursued by the world’s leading chief executive officers in an attempt to provide guidance to new chief executives of today. Considers the marketing strategies employed, together with the organizational structures used and looks at the universal concepts that can be applied to any product. Uses anecdotal evidence to formulate a number of theories which can be used to compare your company with the best in the world. Presents initial survival strategies and then looks at ways companies can broaden their boundaries through manipulation and choice. Covers a huge variety of case studies and examples together with a substantial question and answer section.

This paper aims to quantify the dependence relationship of bat algorithm’s (BA) behaviour on the factors that could possibly affect the outputs, and rank the importance of the various uncertain factors thus suggesting research priorities.

This paper conducts a sensitivity analysis based on variance decomposition of factors in both of original and improved BA. The data sets for sensitivity analysis are generated by optimal Latin hyper sampling in the design of experiment. The optimal factor sets are screened by stochastic error bar measures for the effective and robust implementation of BA.

The paper reveals the inner dependent relationship between factors and output in both of original and improved BA. It figures out the weakness in original BA and improves that. It suggests that uncertainty brought about by factors are mainly caused by the interaction effect and all the higher-order term in sensitivity indices for both of original and improved BA. It ranks the main effect and the total effect of factors and screens out some optimal factor sets for BA.

This paper quantifies the dependence relationship of BA’s behaviour on the factors that could affect outputs using sensitivity analysis based on variance decomposition.

This study aims to improve the bat algorithm (BA) performance for solving optimization problems in electrical engineering.

For this task, two strategies were investigated. The first one is based on including the crossover technique into classical BA, in the same manner as in the genetic algorithm method. Therefore, the newly generated version of BA is called the crossover–bat algorithm (C-BA). In the second strategy, a hybridization of the BA with the Nelder–Mead (NM) simplex method was performed; it gives the NM-BA algorithm.

First, the proposed strategies were applied to solve a set of two standard benchmark problems; then, they were applied to solve the TEAM workshop problem 25, where an electromagnetic field was computed by use of the 2D non-linear finite element method. Both optimization algorithms and finite element computation tool were implemented under MATLAB.

The two proposed optimization strategies, C-BA and NM-BA, have allowed good improvements of classical BA, generally known for its poor solution quality and slow convergence rate.