ESIC Market

Development and validation of Brand Strategies Evaluation Scale for Mobile Network Users

Kamran Khan*

PhD Scholar

Department of Management Sciences, COMSATS University Islamabad. Pakistan, phdmanagement.hrm@gmail.com

https://orcid.org/0000-0002-3134-1727

Ather Mujitaba

Center for Mind/Brain Science CiMeC, University of Trento. Italy, mujtaba_ather@yahoo.com

https://orcid.org/0000-0002-6239-2420

Received: 21-06-2022; Accepted: 17-08-2022; Published: 31-01-2023

Abstract

Purpose: Mobile network operators (MNO) use a variety of brand strategies in the Pakistani telecommunication market to entice mobile network users (MNU), but there was no standardized measure available that provides a fixed set of criteria for their brand strategies. To fill this knowledge gap, the primary goal of the current study is to design, develop and validate the Branding Strategies Evaluation Scale (BSES).

Design/methodology/approach: The mixed-methods model of scale development and validation was employed in various phases by splitting into two studies. In study 1, after piloting factorial validity of 23 items were surveyed on the sample of 150 conveniently available participants (90= male, 60= female) between ages ranging 16 to 52 years, of different mobile network users

Findings: Exploratory factor analysis unfolded five sub-factors of brand strategies with a high-reliability coefficient and internal consistency, including offer and services, competitive features, advertising strategies, brand identity and facilitation with money matters. The mean gender difference was observed only on the subscale of facilitation with money matters. In Study 2, the convergent validity of BSES was found significant by weighing its positive association with the Customer-Based Brand Equity Questionnaire (CBEQ). While the Customer Switching Intention Scale (CSIS) was used to determine BSES's discriminant validity, which revealed a significant negative correlation between the two measures. However, this is the first study intended to develop a standardized instrument for brand strategy evaluation of MNO.

Practical implications: The results of this research enable Mobile network operators (MNO) to understand what kind of branding strategies are useful and effective for customers. This measure will provide authentic understanding to local MNO about the effectiveness of their brand strategies from consumer perspectives. Likewise, for academics, current research provides a gateway to asses customers' choices in a broader way in different regions for brand preferences and branding strategies used by different cellular companies.

Keywords: Brand strategies evaluation; scale development; mobile network users; advertising strategies

JEL codes: M31; M3

移动网络用户品牌策略评价量表的开发和验证

文章摘要

研究目标： 在巴基斯坦电信市场上，移动网络运营商（MNO）使用各种品牌策略来吸引移动网络用户（MNU），但没有一套固定的标准来为其品牌策略提供一个统一化的衡量。为了填补这一知识空白，本研究的主要目标是设计、开发和验证品牌战略评价量表（BSES）。

分析方法: 在不同的阶段，我们采用了混合方法的量表开发和验证模式，分为两种研究。在研究一中，经过前期研究后，对不同移动网络用户的150名参与者（90名男性，60名女性）进行了23个项目调查，这些参与者的年龄在16到52岁之间。

调查结果: 探索性因素分析显示，品牌战略的五个子因素具有较高的可靠性系数和内部一致性，包括产品和服务、竞争特征、广告策略、品牌识别与金钱方面的便利性的问题. 只有在金钱方面的便利性子量表上观察到了平均性别差异。 在研究二中，通过权衡BSES与基于顾客的品牌资产问卷（CBEQ）的正相关，发现BSES的收敛效度是显著的。而客户转换意向量表（CSIS）被用来确定BSES的判别效度，结果显示这两个量表之间存在明显的负相关关系。但是，这是第一个旨在为移动互联网品牌战略评估开发标准化工具的研究。

实际应用： 这项研究的结果使移动网络运营商（MNO）真实的了解什么样的品牌战略对客户有用和有效。这一措施将为当地的移动网络运营商提供便利，从消费者的角度了解其品牌战略的有效性。同样，对于学术界来说，目前的研究提供了一个门户，可以在不同地区以更广泛的方式评估客户对不同手机公司的品牌偏好和品牌策略的选择。

关键词：品牌战略评估；规模发展；移动网络用户；广告战略。

JEL 代码： M31; M3

1. Introduction

A brand is a kind of product or service produced by an enterprise. It must have a specific name which belongs to a particular company and its identity (Misra et al., 2021). A brand is an asset of the firm by conditional, legal and intangible aspects. A combination of elements or components including a name, URL, logo, term, sign, signal, character, spokesperson, icon or design, or blend of these, is planned to recognize the goods and aids of one company or group of businesses to distinguish them from their contestants (Bennet, 1995).

Whereas, brand strategies are the efforts by the companies to create a unique name for their products and develop a framework for the customer to choose products and services (Alizadeh et al., 2014). The brand strategy could be understood in terms of firms planning to blend and compile their product name for their brand (Laforet & Saunders, 1999) which they present to customers for promoting a specific brand or product (Aaker, 2004). It encompasses the core of the whole marketing strategy and fosters a brand culture for the achievement of business objectives (Holt, 2002). However, a successful brand strategy that increases the demand and thrives the business is an arousing and systematic process. The world of branding is controlled by innovative aspects of advertisement and other marketing strategies. Brand strategy should be tailored with economic metrics, not only by implementing a creative marketing process but also by harmonising with a business model. Thus, brand strategies began with customer preference, then it is co-operated with other business models to gain customer confidence (Almquist & Dor-Ner, 2012).

Digital transformation has changed the marketing path. Companies use digital channels and processes to set branding strategies and retain customers of mobile network operators. Adoption of attractive branding strategies could be beneficial for customer satisfaction and shaping their response towards its operator, (Joshi et al., 2022). Cellular operators have focused on network function virtualization to convey brand effectiveness and make customers loyal. The future era of research of cellular companies can investigate the load factor, network speed and data properties for developing branding strategies and customer satisfaction, (Qureshi et al., 2022). The study of Safeer et al. (2022) examined the effects of the perceived localness and global brand on customer buying behaviours intentions and suggest future studies on emerging markets for judging branding strategies.

Develop and validate self-report measures that would be able to evaluate the various branding strategies used by Pakistani mobile network operators from a consumer’s perspective. The following objectives will be achieved in this study.

1. To develop an indigenous self-report scale that would be able to evaluate the various branding strategies used by Pakistani mobile network operators.

2. To determine the psychometric properties of a newly developed scale.

3. To collect and establish gender-specific norms for a newly developed scale.

4. To establish convergent and discriminant validity of a newly developed scale.

2. Literature Review

The available literature suggested that the Pakistani mobile network operating sector is a sector where consumers have available services from several competitors. These operators are eager to distinguish themselves from their rivals in a unique way to attain a strong position in the market. The study of Aslam and Frooghi (2018) elaborates five cellular companies compete with each other in Pakistan to retain maximum numbers of customers. To bring long-term profitability, these companies are focusing on customer loyalty and are using different marketing strategies. Similarly, the research of Hassan et al. (2013) discusses mobile network operators introduce a range of approaches to attract their customers. The selection process is based on, a monthly commitment of customers toward mobile network operators, monthly accusations, returns offering and value-added services provided by a mobile network operator. Monthly charges included monthly fees that users pay to their network operators. Rewards refer to special benefits offered by mobile network operators during a particular period and value-added services included all extra services provided by mobile network operators. Strong advertising and marketing strategies lead to customer brand awareness. Publicity strongly affects consumer choices, so all of these companies allocate their large amount of budget the advertisement. Perfect Competition compels every cellular company to launch strong and efficient branding strategies for better outlook representation than competitors (Butt & Run, 2009). Some other studies explained further features of MNO brand strategies, which are more or less adopted by most of the operators such as signal and voice quality, internet connectivity, call rates, and complaint response. If the mobile network operators satisfy the consumers by providing the above-described services, this leads to customer satisfaction with a specific brand, (Kataria & Saini, 2019).

Customer fulfilment was grounded to be vastly related to the customers’ perception of services provided by mobile network operators (Hanif et al. 2010). Conscientious brand is one of the factors that create satisfaction among customers; customers satisfaction is established if the product or service fulfilled their desired requirements. Likewise, price fairness and customer services lead to consumer gratification in the telecommunication sector. Therefore, MNO in Pakistan focuses on better network coverage, viable pricing and varied offering to retain existing consumers and up-gradation of quality to attract new customers (Khan, 2010). The review of literature rectifies the ample need for standardized measures for MNO brand strategies because available explanations are contrasting, overlapping and sometimes unable to yield a precise explanation of the brand strategy of MNO. In addition to this, instruments used in available studies were not standardized that even making it difficult to precisely conceptualize the MNO brand strategies and their interrelated factors. Therefore, this scale will be a leap forward in marketing research on MNO, it will help to build evidence-based set criteria of branding strategies evaluation of MNO for MNU, which will be assimilated to the local telecom market's needs. However, the mixed-methods model is chosen for the development and validation of this scale and it will be constituted in the following phases, an idea for the new measure, substantive validation phase(finding the construct, initial items pool, piloting), structural validity phase(finding psychometric evaluation, provisional scale extraction), external validity phase (evaluating convergent, discriminant) and finished scale (Simms, 2008; Zhou, 2019).

3. Method

Study 1

Development of the Branding Strategies Evaluation Scale

3.1 Phase 1: Item Generation

Firstly, in-depth interviews were conducted with the marketing managers of five mobile network operators in Lahore city. The study is related to five cellular companies so one representative of each company was selected for interview. The respondents were asked to explain the branding strategies used by their mobile network operator. After listening to all the interviews and looking at the interview notes, a pool of items was extracted for the new scale to be developed during the present study. These themes were matched with existing literature on branding strategies in telecom services. A total of 23 relevant and appropriate items were finalized from the pool of items.

3.2 Phase 2: Pilot Testing

Pilot testing was followed through to certify psychometric screening of the items, eliminating overlapping and elusive items and warrant legibility of items in the scale.

Sample. A sample of 35 consumers of Pakistani mobile network operators was recruited from the city of Lahore (men = 18, women = 17). The age ranged from 18 to 52 years (M = 73.09, SD = 25.4).

3.3 Phase 3: Factor Analysis

In phase 3 factorial validity of the Branding Strategies Evaluation Scale(BSES) was established, to assure the structure of items and retention of final items.

Sample. The sample consisted of 150 individuals recruited from the city of Lahore (men = 90, women = 60). The age ranged from 16 to 55 years (M = 27.02, SD = 8.86) and a convenient sampling strategy was used. Respondents were selected from all categories of life and anyone who was the user of a mobile phone and was accessible was included in the sample.

Ethical Consideration. Before data collection, the study protocol was approved by the University Ethical Review Committee. The review committee carefully assessed during this research and after this study, and none of the ethical concerns would be violated. It was assured that institutional and individual consent form was obtained before data collection.

3.4 Procedure

After pilot testing, the 23-item Branding Strategies Evaluation Scale was filled by the 150 participants of the study who were loomed individually either at their workplace, home or at study place and directed about the tenacity of the study. The measure was circulated among the respondents at their will and respondents filled up the form in one sitting. The number of participants was determined according to the number of items on a scale as it is considered statistically satisfactory if it is higher than 10 participants for each item on the scale (Field, 2009). The initial version of BSES consisted of 23 items so a sample of 150 participants appeared satisfactory (23 x 5 = 115).

3.5 Results

Table 1. illustrates the frequencies and percentages of demographic variables' characteristics. Among total mobile network users sample (N = 150), Ufone users were highest in numbers and percentage (n = 44, 29%), Warid users were second with (n = 36, 24%), Mobilink users were third (n = 29, 19 %), Telenor's users were fourth (n = 27, 18 %) and Zong had least number (n = 14, 9.3 %) of users in total sample. Whereas, male participants had comparatively high proportion (n = 90, 60%) as compare to women (n = 60, 40%) of total sample. The third demographic category was marital status, as a majority of participants were (n = 92, 61.3 %) unmarried, (n = 52, 34.7 %) were married and 4 % did not respond to the question. Furthermore, a comparison of participants' monthly income in Pakistani rupees was also inquired, which indicated (n = 16, 10.7 %) participants earned less than 10,000 monthly. While, round about 50 % participants fall in 11,000 to 25,000 and 26,000 to 50,000 income range. Following to higher income level, (n = 36, 13.3 %) had income between 51,000 and 75,000, (n = 19, 12.7%) earned income between 76, 000 and 100, 000 and only (n = 19, 12.7 %) earned more than 100,000 Pakistani rupees. Only three participants' responses were missing about monthly income.

Running the Factor Analysis. 23 items of the Branding Strategies Evaluation Scale which had been narrowed down after the pilot study was weighted by factor analysis. Construct factor structure was computed after a principal component solution that assisted in driving distinctive items for the final version of the scale. 300 participants' data were subjected to Principal Component Analysis with Varimax rotation. Items chosen to be discarded have a commonality of less than .45, based on a recommendation given by Paunonen and Jackson (2000). Except for one item (no.8), all commonalities met this recommendation. Another reason for removing item 8 was that it clustered together with items 1, 2, and 3 (before its removal) with whom it did not have any logical relation. After removing item no.8, the analysis resulted in a KMO value of .861, indicating the adequacy of the ratio of the number of participants for running a principal-component factor analysis (Kaiser, 1974). The Bartlett test of sphericity was also momentous (p< .001) thus demonstrating an adequate distribution of data. The normality of scores was checked by observing the values of skewness and kurtosis and they were quite satisfactory. To find out and remove any potential outliers, a box plot was computed and it was found that there was no potential outlier. Correlations among items were checked and it was unearthed that all items correlated with each other on an average of .3, which was satisfactory according to Coakes and Steed (2003).

Table 2. The number of eloquent factors was correspondingly finalized by following Kaiser's criterion that resulted in five factors. Subsequent PC analyses were also run using four and three-factor solutions using Varimax rotation. However, it was concluded that the five-factor solution yielded the clearest, logical and interpretable solution without any cross-loading. The five factors were retained based on the screen plot; Eigenvalues > 1.0 and underlying themes. The final items of the scale were chosen on the criterion of having a factor loading of .45 and beyond (Raubenheimer, 2004). As a result of this, only one item (no. 13) did not load on any factor and was thus eliminated from the final version of the instrument. In this way, the final version of the Branding Strategies Evaluation Scale ended with a total of 21 items with a five factors solution. None of the final 21 items demonstrated complex structure. The respondents would have to rate each item on a Likert type ascending order scoring as 1 = Poor, 2 = Fair, 3 = Good 4 = Very Good and 5 = Excellent. Higher scores on the scale would represent a more positive rating of the branding strategies of the respondent's preferred mobile network operator and vice versa.

3.6 Factors of Branding Strategy Evaluation

Factor 1(Offers and Services). The Five items from the original version of BSES (16, 17, 18, 19 and 20) loaded on factor 1 Items loading were .54, .75, .60, .75 and .72 respectively. 34.8 % of the variance is accounted for by this factor.

Factor 2 (Competitive Features).Six items from the original version of BSES (9, 10,11,12,14 and 15) loaded on factor 2. Items loading were .75, .58, .51, .46, .67 and .50 respectively. 9.15 % of the variance is accounted for by this factor.

Factor 3 (Advertising Strategies). Four items from the original version of BSES (4, 5, 6 and 7) loaded on factor 3. Items loading were .60, .60, .54and .78 respectively. 5.89 % of the variance is accounted for by this factor.

Factor 4 (Brand Identity). Three items from the original version of BSES (1, 2 and 3) loaded on factor 4. Items loading were.75, .78 and .68 respectively. 5.52 % of the discrepancy is accounted for by this factor.

Factor-5 (Facilitation with Money Matters). Three items from the original version of BSES (21, 22, and 23) were loaded on factor 5. Items loading were .68, .72 and .56 respectively. 5.04 % of the variance is accounted for by this factor. (See Appendix).

Table 3. shows selected items for each factor in the initial version and final version of BSES. In the final study, selected items for the first factor "Offers and Services" were 14, 15, 16, 17 and 18. The second factor "Competitive features" was ended on six items 8, 9, 10, 11, 12 and 13. The third Factor "Advertising Strategies" retained items were 4, 5, 6 and 7 loaded in the final studies. Thus” Brand Identity factor” was loaded with 3 items 1, 2 and 3 and facilitation with Money Matters factor loading was 19, 20 and 21.

3.7 Phase 4: Determine Internal Consistency of BSES

Table 4. contains a reliability analysis of BSES and its subscales reliability estimates. In this phase, the internal consistency of the Branding Strategies Evaluation Scale (BSES) was determined on the normative sample upon which it was developed (N = 150). The scale had a significantly high-reliability coefficient α = .91 and none of its subscale alpha values was less than .65. The subscales reliability estimates were .84 “Offers and Service”, .81 “Competitive Features”, .72 “Advertising Strategies”, .76 “Brand Identity” and .66 “Facilitation with Money Matters”.

Each item had a significant high (p < .001) association with an aggregated score on the scale. All items were positive and correlate with the total score. The maximum number of item correlations with the total score was above .50 and none of the correlations of the items was below .47.

Each factor was significantly correlated (***p < .001) with the other. The most significant and high correlation was found (.70) between the "Offer and Services" and Competitive Features factors. Offers and Services factor correlation was .40 with Advertising Strategies, .33 with "Brand Identity and .55 with Facilitation with Money Matters. The second factor Competitive features correlation was .45 with Advertising Strategies, .43 with Brand Identity and .54 with Facilitation with Money Matters. The third-factor correlation value was .49 with Brand Identity and .33 with Facilitation and Money Matters. Brand Identity was a comparatively low correlation of .23 (p < .01) with Facilitation and Money Matters than other factors.

The correlation values of each factor with the total scale were high (above .60) and significant (p< .001). The first two factors Offers and Service and Competitive features had correlation values of .84 and .87. Advertising Strategies and Facilitation with Money Matter correlated at .70 and .68. The Brand Identity factor correlation value of .61 was the lowest among the five factors.

3.8 Phase V: Development of Norms

Norms indicated a significant mean gender difference on the sub-scale of facilitation of money t (148) = 2.12, p< .05. There were no other significant gender differences on the remaining score comparisons.

Study 2

Establishing the Validation of the Branding Strategies Evaluation Scale

This study was conducted to ascertain the convergent and discriminant validity of the newly developed Branding Strategies Evaluation Scale.

3.9 Part 1: Establishing the Convergent Validity Method and Sample

A sample of N = 110 students was recruited from the Government College University, Lahore (men = 47, women = 63). The age of the respondents ranged from 18 to 32 years. The Convenient sampling strategy was used.

3.10 Instruments

1. Branding Strategies Evaluation Scale(BSES)

2. Customer-Based Brand Equity Questionnaire(CBEQ). Dass and Jansson (2012) developed the Brand Equity Questionnaire for their research on Swedish mobile network operators. The questionnaire has five subscales: brand awareness, brand associations, perceived quality, brand loyalty, and brand trust and consists of 22 items. The respondents have to rate to what degree (on a Likert scale where 1=do not agree at all and 7=fully agree) they agree with an item. Higher scores on the scale, are indicative of higher brand equity.

3.11 Results

In part 1 of study 2, the convergent validity of the Branding Strategies Evaluation Scale was established by estimating association vis-a-vis with the Customer-Based Brand Equity Questionnaire. The Cronbach's Alpha values of the Branding Strategies Evaluation Scale and the Customer-Based Brand Equity Questionnaire for the study's sample (N = 110) were .88 and .92 respectively.

A substantial positive correlation between the total scores of the Branding Strategies Evaluation Scale and the total score of the Customer-Based Brand Equity Questionnaire was found (r = .45, p< .01). A significant positive correlation between four sub-scale scores (out of five) of the Branding Strategies Evaluation Scale and the total score of the Customer-Based Brand Equity Questionnaire was found. These sub-scales were offer and services (r = .48, p < .01), competitive features (r = .40, p < .01), brand identity (r = .20, p < .05) and facilitation with money matters (r = .36, p < .01). The only sub-scale that did not have a weighty positive correlation with the Customer-Based Brand Equity Questionnaire was advertising strategies (r = .04).

3.12 Part 2: Establishing the Discriminant Validity of the Branding Strategies Evaluation Scale Sample Method

A sample of N = 110 students was recruited from the Government College University, Lahore (men = 47, women = 63). The age of the respondents ranged from 18 to 32 years. Convenient sampling was employed for the selection of the sample consisting of individuals who were users of a Pakistani mobile network. In inclusion criteria, it has been assured that those participants were included who are mobile users for six months.

3.13 Instruments

1. Brand Strategies Evaluation Scale (BSES)

2. Customer Switching Intention Scale (CSIS). The scale was developed by Shin and Kim (2008) to measure customer switching intention in mobile number portability. The Customer Switching Intention Scale has three items and the respondents have to rate to what degree (on a Likert scale where 1=Strongly Disagree and 7=Strongly Agree) they agree with an item. Higher scores on the scale represent a stronger desire to switch to a brand currently in use.

3.14 Results

In part 2 of study 2, the discriminant validity of the Branding Strategies Evaluation Scale was determined by evaluating its correlation with the Customer Switching Intention Scale. The Cronbach’s Alpha values of the Branding Strategies Evaluation Scale and the Customer Switching Intention Scale for the study’s sample (N = 110) were .88 and .81 respectively.

As predicted, a significant negative correlation between the overall scores of the Branding Strategies Evaluation Scale and the total score of the Customer Switching Intention Scale was found (r = -.22, p < .05). A negative correlation between four sub-scale scores (out of five) of the Branding Strategies Evaluation Scale and the total score of the Customer Switching Intention Scale was found. These sub-scales were offer and services (r = -.28), competitive features (r = -.17), brand identity (r = -.09) and facilitation with money matters (r = -.15). A significant negative correlation between offers and services and the total score of the Customer Switching Intention Scale was found (r = -.28, p < .0). The only sub-scale that did not have a negative relationship with the Customer Switching Intention Scale was advertising strategies (r = .01).

4. Discussion

The study aimed to develop and validate a self-report scale for Pakistan's mobile network operators in the context of a consumer perspective. Scale Development and validation have been divided into two studies. Study 1 was completed in five phases which were initiated with the generation of items pool for scale. Intensive interviews were conducted with five managers of different mobile companies for gathered data. Based on collected data, an items poll was generated that was further rated by different mobile users on the Likert scale. Only 23 highly-rated items were selected for piloting. A pilot study was conducted on 35 mobile network users (men = 18, women = 17) whose age ranged from 18 to 52 years (M = 73.09, SD = 25.4). Initial analysis and respondent responses were keenly observed to assess participants for any ambiguity or confusion about BSES items.

In the third phase, BSES was administered to a sample of 150 (90 = Male and 60 = female) participants of different mobile network users between ages ranging 18 to 52 years. Exploratory factor analysis Verimax rotational method was used to extract factors from the Brand Strategies Evaluation Scale. It was finalized with 21 items after factor analysis with five well-defined factors (offer and services, competitive features, advertising strategies, brand identity and facilitation with money matters). The Cronbach's alpha coefficient for Branding Strategies Evaluation Scale was α = .91 while Cronbach's alpha coefficients for sub-scales ranged between α. = .66 (Facilitation with Money) to α. = .84 (Offers and Services). An approximation of item to total correlation conceded that all the items were absolutely and distinctively correlated with the total score. There was also a high positive inter-correlation between unlike subscales of BSES. The scores of men and women were compared on the sub-scales and total scores of BSES. Results indicated a significant mean gender difference on the sub-scale of “facilitation of money matters”. No other significant gender differences were found.

Study 2 was conducted to gauge the convergent and discriminant validity of the indigenously developed BSES. The convergent validity of the BSES was established by getting the measure of its correlation with the Customer-Based Brand Equity Questionnaire. A substantial affirmative correlation between the total scores of the Branding Strategies Evaluation Scale and the total score of the Customer-Based Brand Equity Questionnaire was found (r = .45, p < .01). The discriminant validity of the Branding Strategies Evaluation Scale was made out by evaluating its correlation with the Customer Switching Intention Scale. A significant negative correlation between the total scores of the Branding Strategies Evaluation Scale and the total score of the Customer Switching Intention Scale was found (r = -.22, p < .05). These findings have demonstrated the psychometric strength of the newly developed indigenous scale.

5. Conclusion

It has been explored in this study that Brand strategy is accompanied by five components “Offer and Services, Competitive Features, Advertising Strategies, Brand Identity and Facilitation with Money Matters. These are essential in brand strategies that have been proven with constructing BSES. Factor loading compilation is evident of valid five-component BSES and Correlation analysis is presented that all factors are significantly correlated to explain the same construct. BSES convergent and discriminant validity has also been well-defined for further use of scale in other studies and further research use. Moreover, this study has provided a theoretical understanding of the organization of brand strategies.

5.1 Implication

There are two broader implications of this study. First, this is an indigenous measure for quantifying brand strategies and it provides valid metrics for mobile network operators (MNO) brand strategies. Secondly, this tool will use for the evaluation of brand strategy in our culture that will yield valuable information about the most effective strategy for mobile network users. Also, based on this valid measure, it will be possible for later researchers to theoretically conceptualize MNO brand strategies on concrete grounds.

5.2 Limitations and suggestions

The main limitation of the study is the sample size which was restricted to a few hundred participants due to the time frame of the study. Moreover, the sample only contained students and people who could comprehend well English, because the scale was in the English language. Furthermore, participants were also recruited from a single university that could be extended to different educational institutes. However, BSES needs to be validated on a bigger sample, a variety of populations and in the Urdu language to make this instrument more effective.

Disclosure Statement

There is no potential conflict of interest among authors.

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Appendix

Brand Strategy Evaluation Scale (BSES)

Instruction

Please evaluate the quality of the following features of your preferred mobile network by choosing the option that best corresponds to you.

Note: Please choose only one of the following mobile network operators for rating all the items.

_______________________________

^* Corresponding author.

Email: phdmanagement.hrm@gmail.com