This study presents the assessment of beef quality determination based on the consumer preferences, established in the beef retailing shops. The aim was to establish correlation between the customers’ preferences and quality attribute cues affecting their preferences. Systematic review approach was used to identify studies connected with beef quality determination, leading to secondary data. The primary data on consumer preferences was collected from 208 and 98 customers in Dar es Salaam and Mbeya cities in Tanzania. Quality attribute cues that impact customer preference were collected using a Likert scale technique and analyzed by using Kruskal-Wallis one way ANOVA by ranks, after checking the reliability by multiple regression model. Tenderness, price, juiciness, breed’s information and fat content were observed to be the five topmost overall ranked quality cues that impact customers’ preferences. With respect to relative ranking, the highest relatively ranked beef quality cues in search, experience and credence attributes were price, tenderness and breed’s information. Based on primary data, the assessed quality cues were positively accepted as the factors that influence consumers’ preferences on butcher’s location (73.5% and 72.6%), personal relation with sellers (69.4% and 69.7%), beef color (70.4% and 70.2%) and fat content (69.4% and 69.2%) in Mbeya and Dar es Salaam, respectively, and noted to be very comparable between the cities. With exception of the photo of choice standard graded beef, the responses of customers in Mbeya were relatively higher than in Dar es Salaam, with type of cut and beef cleanliness being the two highest pointed quality cues.
Beef quality determinants are quality cues that are available in the selling outlet during inference making about beef by customers under the influence cultural and socio-economic diversity [
Customer preferences in beef determination are described based on the meaning of quality as per economic point of view [
Consumer decision making in beef determination involves three main scenarios that were described based on quality attributes that are evaluated by quality cues across search, experience and credence qualities [
In spite of the fact that beef is the third most widely consumed meat in the world [
Search quality | Experience quality | Credence quality | |
---|---|---|---|
Intrinsic cues | Beef color, leanness, marbling, type of cuts, fat, beef cleanliness | Beef color, tenderness, juiciness, flavor, beef cleanliness | Freshness |
Extrinsic cues | Price, Butcher’s location, relation | - | Breed’s information, certification, fat |
based on the eating type of quality that is noted as the most important aspect of beef quality that include overall satisfaction and a function of combined effects of tenderness, juiciness and flavor. Beef quality determination is too complex to appropriately decide as to whether beef in the retailing shops is suitable or not [
In the past, it was argued that food quality specifications are either absent or available but too stringent to be enforced in many countries [
Generally, information and data connected to beef quality was collected through observation by using checklists and beef quality photo as guiding tool. Checklists and beef quality guiding tool were designed based on the identified gap from attention made by beef sellers to the customers in retailing shop as indicated in literature [
In this study, the identified problem of matching beef quality cues and customers preferences on beef suitability was addressed by testing three main hypotheses. These hypotheses were established based on the gaps identified from the reviewed approaches on determination of beef quality in the retailing shops. The first hypothesis was testing as to whether the reviewed search beef quality
cues collectively have an effect to the choice of suitable beef in the retailing shop. In this study, the reviewed search beef quality cues are personal relation (between seller and customer), price, branding/packaging, freshness, marbling and beef presentation/type of cut. Other search beef quality cues in this research are beef color, fat content, butchers’ location, advertisement/promotion, beef cleanliness, beef selling certification and smell (aroma).
The second hypothesis, on the other hand was testing the correlation between customers’ responses on quality attribute cues that impacting their respective preference on beef and their respective choice on the photos of standard graded beef. Whereas, the last hypothesis in this study compared the results between the surveyed cities based on beef quality attribute cues, which were regarded as influencing factors on consumer preferences.
Various studies have been conducted in consumer behavior towards decision making on procuring various products at purchasing points. Most of the studies were comprehensive detail the means in which consumers make decision by involving search, experience and credence quality attributes [
Although the quality of beef is differently interpreted among consumers, nutritional as objective entity and eating quality aspect of quality have been recorded as the most important dimensions in user based quality approach [
Quality in user-based dimension is determined by one among the four main approaches, i.e., economics of information, multi-attribute, hierarchical, and integrative [
On the other hand, the multi-attribute approach of quality determination for a product is considered as a multi-dimensional evaluation, during which, its overall quality is described by a set of cues that are perceived by the consumer [
The next one is hierarchical approach with means-end chain model as a well-established model. This approach describes the means at which consumers infer some attributes from other attributes. The approach is elaborated by the means-end chain model that describes the links, which a consumer establishes between product perceptions and abstract purchase motives or values. For example, a consumer will inspect the color of a piece of meat (a product characteristic) because he believes it to be related to the taste of meat when prepared (expected quality), and the taste will lead to enjoyment while eating (abstract purchase motive). The product attribute (in and by itself) is only relevant to the extent that the consumer expects to lead to one or more desirable or undesirable consequences [
The last one is integrative approach that focuses on the determinants of experienced as opposed to expected quality and the technical product specifications, which will determine both the intrinsic quality cues the consumer can perceive and the quality finally experienced. The approach is silent on credence attributes like safety, environmental quality, and health although they are recognized as important in food choice motivations. This study draws data from consumers’ perceived beef quality as users of the product. Such users were found at points of sale of beef (butchers).
In connection to this, other literature reported the means in which the described inaccuracy in determination of the quality of products is corrected by using the concept of usability [
The determination of beef quality in user-based dimension involves the optimum needs and motivations based on economic and deeper levels involving emotions, cultural norms and values, and group affiliations [
User-based approach is connected to the fact that, any product can be conceived as an array of its related cues during which, each cue provides a basis for various impressions [
Beef-based cuisine | Continents | |||
---|---|---|---|---|
Africa | Asia | Europe | America | |
Grilled | √ | √ | √ | √ |
Deep/stir-fried | √ | √ | √ | √ |
Stewed | √ | √ | √ | √ |
Smoked | × | √ | × | × |
Steamed/braised | √ | √ | √ | √ |
Sausage | √ | √ | √ | √ |
Raw soup | × | √ | × | × |
Burger | × | × | √ | √ |
product, and they are observable prior to consumption [
Quality of use is determined by two main components, namely, product and context in which it is used, i.e., the particular users, tasks and environment [
Currently, the quality of use and or usability is measured by the methods of the European Metrics for Usability Standards in Computing (MUSiC) project
[
The study was carried out in Mbeya and Dar es Salaam and conducted based on the established hypotheses along the pre-slaughtering, slaughtering and post slaughtering chain between January and April 2017. According to 2012 population and housing census, as the Dar es Salaam city with a total area of 1800 km2 has a population of 4.36 million in 2012 United Republic of Tanzania (URT), Mbeya city with 19,098 km2 has a population of 0.69 million. Dar es Salaam and Mbeya cities are characterized by high level of poverty despite the various efforts on interventions. Among other poverty indicators, the difficultness for their respective residents on accessing the basic needs in 2011 was at 5.2% and 24.3% levels, respectively. As Dar es Salaam has six slaughter facilities with capacity to slaughter 720 cattle a day, Mbeya has three slaughtering facilities with daily capacity of 200 cattle [
Quality indicator | Characteristic (s) | Functional group | Chemical compound to be tested | Laboratory testing method |
---|---|---|---|---|
Flavor | Sweetness | Carbohydrate (sugars) | Glucose, fructose and ribose | Liquid Chromatograph with Mass Spectrum Detector (LC-MSD) |
Protein (Amino acids) | glycine, alanine, lysine, cysteine, methionine, glutamine, succinic | Gas Chromatograph with Mass Spectrum Detector (GC-MSD), | ||
Organic acids | glycine, alanine, lysine, cysteine, methionine, glutamine, succinic | |||
Sourness | Protein (Amino acids) | lactic, inosinic, orthophosphoric & pyrrolidone carboxylic | ||
Organic acids | Succinic, lactic, inosinic, ortho-phosphoric and pyrroldone carboxylic | |||
Bitterness | Hypoxanthine | Hypoxanthine | ||
Protein (Amino acids) | Arganine, leucine, tryptophan anserine and carnonsine | |||
Meaty | Denaturing | 4-hydrox-5-methyl-3(2H)-furanone (HMF) | Ultra violet-visible r (UV-VIS) Spectrophotomete | |
Meat color | Dark, red, pink and colored | Water holding capacity | Ultimate pH | pH meter |
Protein (Amino acids) | Myglobin | GC-MSD | ||
Lipid (Fatty acids) | Linoleic acid | |||
Organic acids | Lactic | |||
Anti-oxidants | Vitamin E | LC-MSD | ||
Transition Metals | Copper, iron | Atomic absorption Spectrophotometer (AAS) | ||
Tenderness/texture | Toughness | Amino acids | Amino acids | GC-MSD |
Organic acids | Lactic | |||
Fatty acids | Linoleic acids | |||
Water holding capacity | Ultimate pH | UV-VIS Spectrophotometer |
Dar es Salaam city was selected because of its unusually high population due to its metropolitan characteristics which attract many people looking for employment in the industries. Mbeya city was also targeted due to the availability of consumers from working that includes government departments, Institutions, private companies and entrepreneurs [
Beef quality determination indicators were formulated based on the data that were collected from both secondary (assessment of literature records) including scientific reviews and research articles and primary sources of information (field data collection) as conceptualized in the data gathering model in
In this research, secondary data were collected from literature by using systematic review approach in which a number of scientific publications were reviewed in connection to their respective relevancies focusing on the study matter. In the systematic review, literature were organized to not only the classes (scientific articles and reviews), but the number of publications that detailed quality cues that impact customers preferences on beef in a consolidated standard of reporting trials (CONSORT) flow diagram. The final results in connection to the secondary data were presented in clustered columns of quality attribute cues across the search, experience and credence attributes. Primary data, on the other hand, were collected from beef retailing shops by recording the customers’ opinion on the photo of standard graded beef and a provided list of quality attribute cues that impact customers’ preference on beef. This type of data was further recorded in clustered columns that were plotted as percentage
of customers against their degree of acceptance on the assessed stimuli (photo of standard graded beef and a list of quality cues). The final data type resulted from statistical analysis which was presented in figures and tables before drawing the final conclusion.
This study on beef quality preferences were conducted by interviewing the purposively identified customers at different beef retailing shops that were conveniently selected from a list of pre-inspected food processing units. In this respect data connected with thirteen (13) beef quality cues in search quality attribute as reported in literature [
In this study, checklists were designed for recording the ranked responses from beef consumers in the pre-listed statement based on the Likert scale technique. It is empirical study that was designed based on the gaps identified by the past work against the similar problem, and have not yet been examined [
The compiled responses of consumers based on Likert items with respect to the portrayed photo and search beef quality cues were analyzed after checking their reliabilities by Multi-linear regression analysis in the Spread sheet of Microsoft Excel version 2010 to both identify predictor variables (search beef quality cues) and their multicollineality effect During this study, multi-linear regression model was also used in comparing the customers’ decision on the portrayed photo based on their responses on the search beef quality cues between the surveyed cities. In this regards, the null hypothesis, that states that all beef quality cues collectively have no effect on the decision made during beef quality determination in retailing shops, i.e., the coefficient of beef quality cues, denoted as βi, as in Equation (1) are the same.
H o : β 1 = β 2 = β 2 = ⋯ = B p
Rejection of this hypothesis leads the testing as to whether the individual regression coefficients are significant while controlling other variables in regression model.
In addition to that, Kruskal-Wallis one way ANOVA by ranks test statistic was used to test whether the consumer preferences in the surveyed cities are statistically comparable as the data involved are non-parametric. The testing was involved the checking on the possibility of having statistical difference on rating the named indicators by consumers grouped based on the streets of the surveyed cities at 0.05% significance level (95% confidence interval) [
In this part of the study, beef quality attribute cues were identified, listed and analyzed in connection to consumers’ preference from literature. Consumer preferences on beef varieties have been detailed by many studies in terms of scientific reviews and articles around the world. In this study, systematic review was used to both identify these studies and organize the outcomes in a comprehensive interpretation on the beef quality attributes cues those impacting consumers’ preferences. Systematic review that describes it as the transparent and systematic process rather than specific method for data aggregation and interpretation was carried out following five main steps [
In the first step, the focus question was stated as a query in free form before explicit structured by relating its components and designed. As it was mentioned in literature [
1ScienceDirect (https://www.sciencedirect.com/).
2HINARI Access to Research in Health Programme (http://www.who.int/hinari/en).
3Access to Global Online Research on Agriculture (http://www.fao.org/agora/en).
Relevant studies were identified in the second step, an activity that between January and April 2017 from ScienceDirect1, HINARI2 and AGORA3 websites that provide subscription-based to a large database of scientific and medical research licensed at TFDA Offices during which more than 13 million documents and 30,000 e-books were accessible. This was comprehensively and unbiased conducted by using key word identification, search strategies for multiple databases, and hand search journals as shown in other studies [
4Is an industry standard tool for publishing and managing bibliographies, citations and references on the windows and Macintosh.
5Is calculated by counting the number of publications for which an author has been cited by other authors at least that same number of times (this means that the scientist has published at least 20 papers that have each been cited at least 20 times).
In the next step, the records were classified into reviews and research articles, the classes that were applicable for identification and relative ranking of beef quality attribute cues, respectively. The identified reviews were assessed by reading title and abstract before classifying them based on either only one beef quality attribute cue in detail was considered or several attribute cues simultaneously. The full texts of the identified and separated reviews were analyzed for their relevance and quality. Quality was analyzed based on the key sources, clarity and comprehensive description of the argument and novelty in the reviews. Similarly, the list of the selected research articles was obtained by using the same process as in the selection of appropriate citations for the reviews.
Research articles that describe relative importance of different quality indicators from consumer perspective were then identified. The identified articles were further refined based on the described ranking procedures to remain with papers that are clear enough to quantify relative ranking of indicators. Beef quality determination indicators explored from the refined papers were next classified based on search, experience and credence quality and their individual importance within each study was re-scaled as per steps indicated in
Step | Activity |
---|---|
Ranking indicators within articles | The observed indicators were ranked starting with 1, for the least important one to the given maximum level in the article. |
Re-scaling the previous ranking | The ranked indicators were re-scaled from 1, for the least important indicator within the article to 3 for more important indicator within the article based on Equation (1). |
Strengthening indicators by using arbitrary factor based on the number of indicators considered within the paper. | A factor of 1 was given for the minimum 2 indicators and 3 to the maximum number of 16 indicators that was presented across all papers based on Equation (2). |
Scoring within a paper | Equation (3) |
Scoring for individual indicators | The final score (fs) for individual indicators was obtained as a sum across all papers |
The previous ranking, RR, was re-scaled from 1 (as the least important indicator within the article) to 3 (more important indicator within the article) based on Equation (1).
R R = 1 + [ ( 3 − 1 ) ( m l − 1 ) ] × ( g l − 1 ) (1)
Equation (1). Rescalling the previous ranking
In this regards, ml, indicates maximum level of indicators, gl, shows a given level of indicator (The number of levels in this equation is not necessarily the same as the number of indicators if some indicators had the same score.
n i f = 1 + [ ( 3 − 1 ) ( m i − 2 ) ] × ( n i − 2 ) (2)
Equation (2). Determination of number of indicators factor nif, where, mi, maximum number of indicators in the reviewed paper, ni, number of indicators given in the reviewed paper.
f s = 1 + ( R R × n i f )
Equation (3). Final score, fs of each quality cue within a reviewed scientific publication.
In the final step, data were synthesized in a tabular summary of the all the surveyed studies related to each of the key quality attribute cues across search, experience and credence identified as important and facilitate analysis of comparison across studies form like other descriptive synthesis. In this respect the gathered data were entered in designed database in Microsoft excel version 2010 software before being analyzed and interpreted. Data were further presented in a tabular summary indicating beef quality attribute cues, connected with scientific publication reviewed and their respective ranking in figures as clustered columns. Since this is observational study, data were written up in CONSORT) flow diagram as indicated in other studies [
Beef quality attribute cues that impacting consumer preference explored from secondary sources of information were presented across the five main steps of systematic review. First, it includes the focus question, which is asked that ‘is the customers’ choice on a photo of standard graded beef similar to their responses on quality attribute cues that impacting their preferences’.
In line with this question, the structured components are: customers that responded on both photo of beef and quality attribute cues were noted as the population of interest; photo of USDA standard graded beef, was expressed as an intervention of interest; beef quality attribute cues, were explained as the comparator of interest; and customer preferences were outcome of interest. Then, results with respect to second to the final steps of the systematic review processes were presented in CONSORT diagram as shown in
In the flow a list of 930 duplicates was excluded from 3199 records that were obtained from ScienceDirect, HINARI and AGORA by using EndNote. The systematic review was further, elaborated the means in which, a list of 1971 citations among of 2269 records was identified as irrelevant, hence excluded and remaining with a total of 298 documents. The remained records were further classified into 79 reviews and 219 research articles. The assessment and classification of reviews as per either only one indicator in detail or several indicators simultaneously involved resulted to a total of 5 reviews. Similarly a total of 18 articles addressing several indicators were selected for ranking and excluding 32 that dealt with 1 - 2 indicators. Fifty three articles that contained information on relative importance of different beef quality determination indicators as per consumers’ perspective were initially identified. Among the identified papers, 32 were excluded in ranking due to the ambiguous on ranking of the identified indicators. The remaining 28 publication papers resulted to a total of 25 quality attribute cues that impacting customers’ preferences whose individual importance within each study was rescaled as shown in
The identified quality attribute cues that affecting customers’ preferences on beef were ranked based on their relative positions and percentage of scientific
Quality attribute | Indicators | Scientific Review (s) | Research Article (s) |
---|---|---|---|
Search | Personal relation (seller and customer) | [ | [ |
Price | [ | [ | |
Branding/packaging | [ | [ | |
Freshness | [ | [ | |
Marbling | [ | [ | |
Beef presentation/type of cut | [ | [ | |
Beef color | [ | [ | |
Fat content | [ | [ | |
Butcher’s location | [ | [ | |
Advertisement/ promotion | [ | [ | |
Beef cleanliness | [ | [ | |
Beef selling certification | [ | [ | |
Smell (aroma) | [ | [ | |
Experience | Taste | [ | [ |
Tenderness | [ | [ | |
Juiciness | [ | [ | |
Flavor | [ | [ | |
Convenient (availability) | [ | [ | |
Credence | Pathogen | [ | [ |
Nutritious | [ | [ | |
Chemical residues | [ | [ | |
Breed’s information/races | [ | [ | |
Animal age | [ | [ | |
Traditional image | [ | [ | |
Sex | [ | [ |
publication referred. In connection to this,
The final score for individual beef quality attribute cues were presented in terms of both overall ranking and relative ranking in ascending order across all quality attributes search, experience and credence as shown in
Analytical results in this study is similar to other literature [
This is a measure of how important each characteristic is to the respondent’s overall preferences [
is high quality with less marbling than prime and it is widely available meat in carcasses enough to contribute 53.7% of the fed cattle total. In addition to this select beef was noted as uniform quality and normally leaner than prime and choice. It was indicated that there is dissimilarity of preferences as select and choice were separately identified as the best among the displayed pieces of beef by 42.9% and 40.4% of the visited consumers in Mbeya and Dar es Salaam, respectively. Choice and prime in the portrayed photo were similarly pointed each one by 28.6% of the consumers in the visited meat retailing shops at Mbeya.
The responses on the displayed pieces of beef in the visited cities were also reported in other literature [
Price is presented as one of the extrinsic quality attribute cues that affect consumers’ preference on beef during purchasing in the retailing shops. Results in connection to this parameter were presented while assuming that the price of beef as the main factor that influencing customers at purchasing decision. It is a distribution of consumer responses on the price of beef as quality cue impacting their preferences in levels of acceptance as shown in
Similar result were reported in other literature [
The location in which beef retailing shop is found is indicated as one of the indicators for beef quality determination in this study. Evaluation results with respect to this parameter were presented under assumption that it was the main factor to be referred during purchasing decision. It is arranged according to the responses of customers on the location of butcher as the main beef quality cue affecting their preferences in degree of acceptance as shown in
Location as an indicator for beef quality determination is presented during which, about 72.7% and 73.5% of visited consumers in Dar es Salaam and Mbeya, respectively, were positively accept it as reliable extrinsic cue. This parameter is absolutely not accepted by 27.5% and 26.5% of customers as quality determination indicator in Dar es Salaam and Mbeya, respectively. It is also noted that 6.3% of the consumers in Dar es Salaam were absolutely rejected location as an appropriate indicator for beef quality determination. The same composition of consumers in Dar es Salaam was accepted location as the highest for beef quality in meat retailing shops. On the other hand, this parameter was both absolutely rejected and very positively accepted in Mbeya as appropriate
beef determinant indicator by 7.1% and 12.2% of the visited consumers, respectively. This study supports [
Personal relation between sellers and consumers in beef retailing was noted as one of the consumer influencing factor on their respective preferences on beef. The assessment of this parameter was presented as the major factor that influencing consumer preference on beef. It is a customer’s responses on their respective personal relation with sellers as the top most influencing factor distributed in the degree of agreement as shown in
The strength of relation is observed to be about 69.7% and 69.3% of visited consumers in Dar es Salaam and Mbeya, respectively, which positively accept it as reliable beef quality determinant. This quality determination indicator is absolutely not accepted by 30.3% and 30.7% of customers in Dar es Salaam and Mbeya, respectively. On the other hand, approximated discrepancy of 10% of the
consumers is observed in terms of both absolutely rejection and acceptance relation as the highest determinant. The findings of this research are similar to earlier studies that consider personal relationship as one of the beef quality determination indicator in which consumers place much value on being served by butchers of the same ethnic race and religion in traditional market [
Beef color is presented as one among the quality attribute cues that influencing customers’ decision at purchasing outlets. The evaluation results in connection to this parameter was indicated as the highest criteria that affecting the customers’ preferences on meat in the retailing outlet. The assessment of this parameter was presented as the major factor that influencing consumer preference on beef. It is a customer’s responses on beef color as the most important influencing factor arranged in the degree of acceptance with respect to Likert item as shown in
The observation of beef color in quality determination is presented during which, about 70% of visited consumers in each of the visited cities, were positively accept it as reliable intrinsic cue. This parameter is absolutely not accepted by 30% of customers as quality determination indicator in both cities. It is also noted that 7.7% of the consumers in Dar es Salaam were absolutely rejected location as an appropriate indicator for beef quality determination. The same
composition of consumers in Dar es Salaam was accepted location as the highest for beef quality in meat retailing shops. On the other hand, this parameter was both absolutely rejected and very positively accepted in Mbeya as appropriate beef determinant indicator by 4.1% and 11.2% of the visited consumers, respectively. Color as beef quality determination indicator is identified as one of the main intrinsic cues in which consumers based on pointing suitable beef in meat retailing shop [
Type of cut of beef is presented as a beef quality cue that influences customers’ preferences on beef in the selling outlets. In this study, type of cut was expressed while assuming that it was the only criteria to be referred at purchasing point. It is a customer’s responses distributed across the degree of acceptance that is appropriate factor that influencing their respective decision as shown in
Type of cut is presented as an indicator for determining beef suitability during which, about 68.4% and 85.7% of visited consumers in Dar es Salaam and Mbeya, respectively were positively accept it as reliable intrinsic cue. This indicator is absolutely not accepted by 31.7% and 14.3% of the visited customers in Dar es Salaam and Mbeya, respectively. The general responses of the consumers on type of cut in beef are not uniform due to the noticeable variation of consumers between the visited cities. This study is in line with other literature [
Beef cleanliness (without blood) is presented as one of main factors that that influencing customers’ preferences on beef in the selling outlets. In this study, beef cleanliness was presented as main quality determinant under ignorance of other quality attribute cues. This is a customer’s responses distributed across the levels of acceptance that beef cleanliness is the main factor that influencing their respective decision as shown in
Indication of beef suitability is presented as per beef appearances during which, about 70.2% and 81.6% of visited consumers in Dar es Salaam and Mbeya, respectively were positively accept it as appropriate intrinsic cue. This indicator is not accepted by 29.8% and 18.4% of the visited customers in Dar es Salaam and Mbeya, respectively. The general responses of the consumers on beef appearances in beef are not evenly distributed due to the observable variation of consumers in the visited cities. Other literature support this study appearance was used as one of the main beef quality determination indicators for fresh meat exposed for retail sale. Additionally, during evaluation, consumers who preferred beef as per marbling were also mentioned appearance as the main determinant for beef quality. It is also indicated that, beef appearance is used as one of the attributes in beef purchasing by consumers during the study of assessing the beef consumer preferences in Ethiopia. As it has been indicated, visual appearance of retail beef influence consumer purchases. Furthermore, this parameter is described as the determinant for beef quality that is positively accepted by many consumers.
Fat content in retail beef is noted as one of the main influences of for determination of beef suitability. This presentation assumes fat content as the only available quality cue to be assessed by consumers in meat retailing shops. The applicability of fat content as determinant of quality in m1eat retailing premises is presented based on the consumers’ responses on the Likert scales on its applicability as judgment criteria. The results are arranged in clustered columns as percentage of consumers’ responses against the categorized Likert scales in
Preference on the retail beef is presented based on fat content during which, about 69% of consumers in each of the visited city were positively accept it as appropriate intrinsic cue. Fat content on the other hand is not accepted by 31% of the customers from each of the visited city. The general responses of the consumers on fat in beef are not evenly distributed due to the observable variation particularly on absolutely rejection and considering fat as the highest determinant in both cities. This is also indicated in literature [
Fat content in retail beef is noted as one of the main influences of for determination of beef suitability. This presentation assumes fat content as the only available quality cue to be assessed by consumers in meat retailing shops. The applicability of fat content as determinant of quality in meat retailing premises is presented based on the consumers’ responses on the Likert scales on its applicability as judgment criteria. The results are arranged in clustered columns as percentage of consumers’ responses against the categorized Likert scales as indicated in
Preference on the retail beef is presented based on certification during which, 60.7% and 65.3% of consumers in Dar es Salaam and Mbeya were positively accept it as appropriate indicator. Retail and beef certification on the other hand is not accepted by 39.5% and 34.2% of the customers in Dares Salaam and Mbeya. Generally, the consumer variation on responses for certification as quality determinant is not high due to the observable range of about 5%. The finding in this research is parallel with literature that indicated non conformances in beef retailing, during which more than half of the surveyed selling points were operated without certification [
Analytical results with respect to the reliability of customers’ responses on the assessed beef quality attribute cues in Dar es Salaam and Mbeya were summarized in ANOVA
With respect to the first hypothesis the output shows that F = 133.8 (p < 2.5 × 10−50) for Mbeya and F = 91.5 (p < 2.8 × 10−75) for Dar es Salaam indicating that we should clearly reject the null hypothesis that beef quality cues collectively have no effect on the decision made during beef quality determination in retailing shops. This situation that is also denoted as (βi ≠ βj) as indicated in
City | df | ss | ms | F | Significance F | |
---|---|---|---|---|---|---|
Mbeya | Regression | 13 | 64.9 | 5.0 | 133.8 | 2.5 × 10−50 |
Residual | 84 | 3.1 | 0.04 | |||
Total | 97 | 68.0 | ||||
Dar es salaam | Regression | 13 | 105.3 | 8.1 | 91.5 | 2.8 × 10−75 |
Residual | 194 | 17.2 | 0.1 | |||
Total | 207 | 122.4 |
Attribute | Coefficient (βi) | Standard error | t statistics | p-value |
---|---|---|---|---|
Intercept | 0.130 | 0.117 | 1.113 | 0.267 |
Personal relation (seller and customer) | 0.016 | 0.015 | 1.057 | 0.292 |
Price | 0.167 | 0.025 | 6.730 | <0.001 |
Branding (packaging) | 0.017 | 0.024 | 0.721 | 0.472 |
Freshness | 0.081 | 0.022 | 3.615 | <0.001 |
Marbling | 0.098 | 0.029 | 3.337 | 0.001 |
Beef presentation (type of cut) | 0.085 | 0.024 | 3.484 | 0.001 |
Beef color | 0.099 | 0.023 | 4.282 | <0.001 |
Fat content | −0.007 | 0.014 | −0.496 | 0.624 |
Butcher’s location | −0.010 | 0.021 | −0.463 | 0.644 |
Advertisement (promotion) | −0.014 | 0.015 | −0.918 | 0.360 |
Beef cleanliness | −0.036 | 0.023 | −1.553 | 0.122 |
Beef selling certification | 0.005 | 0.014 | 0.334 | 0.739 |
Smell (aroma) | 0.004 | 0.014 | 0.284 | 0.777 |
Attribute | Coefficient | Standard error | t statistics | p-value |
---|---|---|---|---|
Intercept | 0.310 | 0.097 | 3.210 | 0.002 |
Personal relation (seller and customer) | 0.119 | 0.079 | 1.515 | 0.134 |
Price | 0.190 | 0.099 | 1.910 | 0.050 |
Branding (packaging) | −0.018 | 0.013 | −1.317 | 0.191 |
Freshness | −0.137 | 0.075 | −1.817 | 0.073 |
Marbling | 0.079 | 0.039 | 2.008 | 0.048 |
Beef presentation (type of cut) | 0.026 | 0.015 | 1.792 | 0.077 |
Beef color | 0.129 | 0.047 | 2.723 | 0.008 |
Fat content | 0.118 | 0.021 | 5.548 | <0.001 |
Butcher’s location | 0.104 | 0.034 | 3.042 | 0.003 |
Advertisement (promotion) | 0.039 | 0.030 | 1.335 | 0.186 |
Beef cleanliness | −0.104 | 0.032 | −3.251 | 0.002 |
Beef selling certification | −0.043 | 0.053 | −0.826 | 0.411 |
Smell (aroma) | −0.065 | 0.093 | −0.697 | 0.488 |
marbling in Dar es Salaam is significant controlling for the variable beef presentation (p = 0.001), as is beef presentation controlling for the variable marbling (p = 0.001).
Looking at individual tests in
The
The data in
Results with respect to the third hypothesis in this study that compared the surveyed cities with respect to customers’ response on beef quality cues against the portrayed photo of beef are presented in
Regression Statistics | ||
---|---|---|
City | Dar es Salaam | Mbeya |
R2 | 0.860 | 0.954 |
Adjusted R2 | 0.850 | 0.947 |
Standard error | 0.298 | 0.193 |
Number of observations | 208 | 98 |
cues, except freshness were responded as appropriate beef quality cues that impacting the preferences of customers in Mbeya at higher rate than in Dar es Salaam.
It was further observed that, the top three highest pointed quality cues were fat content (89.4%), personal relation (88.4%) and beef presentation (type of cut) (85.7%) that were responded in Mbeya. On the other hand, the top three scored quality cues in Dar es Salaam were freshness (79.2%), butcher’s location (72.6%) and beef cleanliness (70.2%) together with beef color (70.2%). Similar to this study, butcher’s location was also reported in literature [
The five topmost documented beef quality cues among all parameters in the reviewed 29 publications which impact consumer preferences are the tenderness, price, juiciness, breed’s information and fat content. The three highest ranked beef quality cues in each of the quality attributes were observed to be price, fat content and smell (aroma) in search attribute; breed’s information, nutrition and chemical residues in credence attribute; and tenderness, juiciness and taste in experience quality, respectively. While price, juiciness and breed’s information the highest ranked quality cues across the search, experience and credence quality attributes, Branding (packaging), flavor and traditional image were observed to be the lowest ranked beef quality cues.
Based on the results, it can be concluded that there is dissimilarity of preferences as select and choice were separately identified as the best among the displayed pieces of beef by 42.9% and 40.4% of the visited consumers in Mbeya and Dar es Salaam, respectively. The choice and prime in the portrayed photo were similarly pointed by 28.6% of the consumers in the visited meat retailing shops at Mbeya. About 36.6% and 28.5% of visited consumers in Dar es Salaam and Mbeya, respectively, did not positively accept the strength of price as a reliable extrinsic cue. While beef price was absolutely not accepted by 27.9% and 12.2% of customers in Dar es Salaam and Mbeya, respectively, more than 65.3% of the consumers accepted and among them, 13.3% and 4.3% accepted it as the highest determinant in Mbeya and Dar es Salaam, respectively.
While 72.7% and 73.5% of customers in Dar es Salaam and Mbeya, respectively, positively accepted butcher’s location as beef quality cue which impacting their preferences on beef, about 27.5% and 26.5% in the respective cities did not. On the other hand, Butcher’s location, was both absolutely rejected and very positively accepted in Mbeya as appropriate beef determinant indicator by 7.1% and 12.2% of the visited consumers, respectively.
Personal relation between sellers and customers was absolutely not accepted as among quality cues that impacts their respective preference on beef by 30.3% and 30.7% of customers in Dar es Salaam and Mbeya, respectively. About 70% of customers in Mbeya and Dar es Salaam, positively accepted color of beef as the one of the quality cues that impact their respective preferences. Moreover, about 7.7% of the consumers in Dar es Salaam absolutely rejected location as a quality cue influencing their preferences on beef.
The type of cut of beef is absolutely not accepted as an impacting beef quality cue by 31.7% and 14.3% of the visited customers in Dar es Salaam and Mbeya, respectively. The general responses of the consumers on type of cut in beef are not uniform due to the noticeable variation of consumers responses especially at doesn’t (3.1% for Mbeya and 24.0% for Dar es Salaam); “Major determinant” (28.4% for Dar es Salaam and 3.1% for Mbeya; and highest determinant (11.1% for Dar es Salaam and 35.7% for Mbeya). Beef cleanliness was not accepted by 29.8% and 18.4% of the visited customers in Dar es Salaam and Mbeya, respectively, while the general responses of the consumers on beef appearances in beef are not evenly distributed especially at absolutely rejection (5.8% for Dar es Salaam and 0.0% for Mbeya).
Preference on the retail beef based on fat content indicated that about 69% of consumers in each of the visited cities positively accept it as quality cue that impact their preferences. The general responses of the consumers on fat in beef were not evenly distributed due to the observable variations, particularly on both absolutely rejection (16.3% for Dar es Salaam and 5.1% for Mbeya) and highest determinant (11.5% for Mbeya and 30.6% for Dar es Salaam).
Certification was positively accepted as appropriate beef quality cue by 60.7% and 65.3% of consumers in Dar es Salaam and Mbeya. However, the consumer variation on responses for certification as quality determinant is not high due to the observable range of about 5% across all the levels agreement from absolute doesn’t to the highest determinant.
Beef cleanliness and type of cut were positively responded as appropriate cues that impacting customers’ preference by high percentage of customers in Mbeya at 85.7% and 82.6%, respectively, than in Dar es Salaam. While all of the assessed quality cues were positively accepted as the factors that influence consumers’ preferences at more than 50%, beef certification was the lowest accepted parameter in the surveyed cities.
Generally, all the assessed beef quality cues were positively accepted as appropriate factors that influence consumers’ preferences at more than 50%, with smell (aroma) being the lowest accepted parameter in the cities. They were collectively affect decision made during beef quality determination in retailing shops with price, color, presentation, freshness and marbling of beef noted to have significant contribution to the consumers’ choice in both cities.
The authors declare no conflicts of interest regarding the publication of this paper.
Mwashiuya, J.T., Manyele, S.V. and Mwaluko, G. (2018) Assessment of Beef Quality Determinants Based on Consumer Preferences. Journal of Service Science and Management, 11, 657-690. https://doi.org/10.4236/jssm.2018.116045